Signal Processing Method, System, Electronic Device, Storage Medium and Product

Abstract

Embodiments of the present application provide a signal processing method, system, electronic device, storage medium, and product. The method includes: obtaining an error signal through an adaptive filter; determining a target weight coefficient of the adaptive filter according to the error signal; configuring the adaptive filter according to the target weight coefficient to obtain a target adaptive filter; preprocessing a pre-obtained attenuation signal to be processed to obtain a digital attenuation signal; sending the digital attenuation signal to the target adaptive filter; and performing convolution processing on the digital attenuation signal through the target adaptive filter based on the target weight coefficient to obtain a target output signal. The present application determines the target weight coefficient according to the error signal through the adaptive filter, and configures the adaptive filter based on the target weight coefficient, realizing automatic configuration of the heavy driver parameters, thereby improving the efficiency and accuracy of signal processing using the heavy driver.

Description

Technical Field

[0001] This application relates to the technical field of signal processing, and particularly to a signal processing method, system, electronic device, storage medium, and product. Background Art

[0002] In modern high-speed signal transmission systems, the integrity and quality of signals are crucial for ensuring accurate data transmission. However, during signal transmission, signals are often affected by both attenuation of the transmission medium and noise, which makes the originally clear signals become blurred, and even the signal quality drops sharply after long-distance transmission. To solve this problem, the Redriver chip emerged. As a key device in the signal transmission path, it can regenerate and enhance signals, effectively improving signal quality and ensuring the stability and reliability of signals during high-speed transmission.

[0003] In the existing methods for processing signals using Redriver chips, the key step is to manually configure the parameters of each key module in the Redriver chip. Specifically, the user needs to manually adjust the parameters of each key module in the Redriver chip one by one, including the equalizer, linear amplifier, and buffer, and test the signal quality at the end of the post-transmission path, and repeatedly manually adjust the parameters of each key module in the Redriver chip until the required signal conditioning effect is achieved.

[0004] However, in practical applications, the above method requires repeatedly manually debugging the parameters of each key module in the Redrvier chip by testing the signal quality at the end of the post-transmission path until the required signal conditioning effect is achieved. The operation process is very cumbersome and cannot guarantee that the signal debugging effect is always ideal and stable. In addition, the subjectivity of manually debugging parameters is relatively strong, and it is difficult to achieve precise adjustment of parameters, which affects the efficiency and quality of signal processing. Therefore, the existing methods for processing signals using Redriver chips have problems of low signal processing efficiency and low accuracy. Summary of the Invention

[0005] In view of this, this application aims to propose a signal processing method, system, electronic device, storage medium, and product to solve the problems of low signal processing efficiency and low accuracy caused by repeatedly manually debugging the parameters of each key module in the Redrvier chip by testing the signal quality at the end of the post-transmission path until the required signal conditioning effect is achieved.

[0006] According to the first aspect of this application, a signal processing method is provided, which is applied to a re-driver. The re-driver includes an adaptive filter, and the method includes:

[0007] Obtain an error signal through the adaptive filter;

[0008] Determine the target weight coefficient of the adaptive filter according to the error signal;

[0009] Configure the adaptive filter according to the target weight coefficient to obtain a target adaptive filter;

[0010] Preprocess a pre-obtained attenuation signal to be processed to obtain a digital attenuation signal;

[0011] Send the digital attenuation signal to the target adaptive filter;

[0012] Through the target adaptive filter, perform convolution processing on the digital attenuation signal based on the target weight coefficient to obtain a target output signal.

[0013] Optionally, the re-driver includes an input buffer stage and a high-speed analog-to-digital converter, wherein the input buffer stage and the high-speed analog-to-digital converter establish a communication connection;

[0014] The preprocessing of the pre-obtained attenuation signal to be processed to obtain a digital attenuation signal includes:

[0015] Perform preliminary filtering on the attenuation signal to be processed through the input buffer stage to obtain a filtered attenuation signal;

[0016] In the case of obtaining the filtered attenuation signal, send the filtered attenuation signal to the high-speed analog-to-digital converter through the input buffer stage;

[0017] In the case where the high-speed analog-to-digital converter receives the filtered attenuation signal, perform signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal.

[0018] Optionally, the determining the target weight coefficient of the adaptive filter according to the error signal includes:

[0019] Determine the square value of the error signal according to the error signal;

[0020] Determine the square expected value of the error signal according to the square value of the error signal;

[0021] Judge whether the square expected value of the error signal reaches the minimum according to the square expected value of the error signal and the pre-obtained square expected value of the next error signal;

[0022] In the case where the square expected value of the error signal reaches the minimum, determine the weight coefficient and use the weight coefficient as the target weight coefficient of the adaptive filter.

[0023] Optionally, obtaining the error signal through the adaptive filter includes:

[0024] Obtaining a desired signal and an actual output signal through the adaptive filter;

[0025] When the adaptive filter obtains the desired signal and the actual output signal, determining the error signal according to the desired signal and the actual output signal.

[0026] Optionally, the re-driver includes a storage control module, wherein the storage control module establishes a communication connection with the adaptive filter;

[0027] Obtaining the desired signal through the adaptive filter includes:

[0028] Obtaining an initial signal through the storage control module;

[0029] When the storage control module obtains the initial signal, using the initial signal as the desired signal and sending the desired signal to the adaptive filter.

[0030] Optionally, obtaining the actual output signal through the adaptive filter includes:

[0031] Obtaining an attenuation signal and the weight coefficient of the adaptive filter through the adaptive filter, where the attenuation signal is formed by attenuation during the transmission of the desired signal in the signal transmission path;

[0032] When the adaptive filter obtains the attenuation signal and the weight coefficient of the adaptive filter, performing convolution processing on the attenuation signal and the weight coefficient of the adaptive filter to obtain the actual output signal.

[0033] Optionally, determining whether the mean square value of the error signal reaches the minimum according to the mean square value of the error signal and the previously obtained mean square value of the next error signal includes:

[0034] Repeatedly executing the steps of obtaining the error signal through the adaptive filter, determining the square value of the error signal according to the error signal, and determining the mean square value of the error signal according to the square value of the error signal to obtain the mean square value of the next error signal;

[0035] If the mean square value of the next error signal is greater than or equal to the mean square value of the error signal, determining that the mean square value of the error signal reaches the minimum;

[0036] If the expected value of the square of the next error signal is less than the expected value of the square of the error signal, it is determined that the expected value of the square of the error signal has not reached the minimum.

[0037] Optionally, after the step of determining whether the expected value of the square of the error signal reaches the minimum according to the expected value of the square of the error signal and the pre-obtained expected value of the square of the next error signal, the method includes:

[0038] In the case where the expected value of the square of the error signal has not reached the minimum, repeatedly execute the steps of updating the weight coefficients of the adaptive filter, obtaining an error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the expected value of the square of the error signal according to the square value of the error signal, and determining whether the expected value of the square of the error signal reaches the minimum, until the expected value of the square of the error signal reaches the minimum, determining the weight coefficients, and using the weight coefficients as the target weight coefficients of the adaptive filter.

[0039] Optionally, the updating the weight coefficients of the adaptive filter includes:

[0040] Predetermine a target gradient and a convergence factor;

[0041] Determine the new weight coefficients of the adaptive filter according to the current weight coefficients of the adaptive filter, the convergence factor, and the target gradient.

[0042] Optionally, the predetermining the target gradient includes:

[0043] Take the square value of any one of the error signals as the instantaneous square value of the error signal;

[0044] Perform an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient;

[0045] Take the approximate gradient as the target gradient.

[0046] Optionally, the re-driver includes a high-speed digital-to-analog converter and an output amplification stage, wherein the high-speed digital-to-analog converter is respectively communicatively connected to the output amplification stage and the target adaptive filter, and the method includes:

[0047] Send the target output signal to the high-speed digital-to-analog converter through the target adaptive filter;

[0048] The high-speed digital-to-analog converter performs signal conversion processing on the target output signal to obtain an analog target output signal, and sends the analog target output signal to the output amplification stage;

[0049] The output amplification stage performs signal amplification processing on the analog target output information to obtain a processed target output signal.

[0050] According to a second aspect of the present application, there is provided a signal processing device, which includes:

[0051] An error signal acquisition module, configured to acquire an error signal through the adaptive filter;

[0052] A target weight coefficient determination module, configured to determine a target weight coefficient of the adaptive filter according to the error signal;

[0053] An adaptive filter configuration module, configured to configure the adaptive filter according to the target weight coefficient to obtain a target adaptive filter;

[0054] A data preprocessing module, configured to preprocess a pre-acquired attenuation signal to be processed to obtain a digital attenuation signal;

[0055] A data sending module, configured to send the digital attenuation signal to the target adaptive filter;

[0056] A target adaptive filter processing module, configured to perform convolution processing on the digital attenuation signal through the target adaptive filter based on the target weight coefficient to obtain a target output signal.

[0057] Optionally, the re-driver includes an input buffer stage and a high-speed analog-to-digital converter, wherein the input buffer stage and the high-speed analog-to-digital converter establish a communication connection;

[0058] The data preprocessing module includes:

[0059] An input buffer stage processing sub-module, configured to perform preliminary filtering on the attenuation signal to be processed through the input buffer stage to obtain a filtered attenuation signal;

[0060] A filtered attenuation signal sending sub-module, configured to send the filtered attenuation signal to the high-speed analog-to-digital converter through the input buffer stage when the filtered attenuation signal is obtained;

[0061] A data analog-to-digital conversion sub-module, configured to perform signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal when the high-speed analog-to-digital converter receives the filtered attenuation signal.

[0062] Optionally, the target weight coefficient determination module includes:

[0063] An error signal squared value determination sub-module, configured to determine the squared value of the error signal according to the error signal;

[0064] The square expected value determination sub-module of the error signal is used to determine the square expected value of the error signal according to the square value of the error signal;

[0065] The square expected value judgment sub-module of the error signal is used to judge whether the square expected value of the error signal reaches the minimum according to the square expected value of the error signal and the previously obtained square expected value of the next error signal;

[0066] The first target weight coefficient determination sub-module is used to determine the weight coefficient when the square expected value of the error signal reaches the minimum, and use the weight coefficient as the target weight coefficient of the adaptive filter.

[0067] Optionally, the error signal acquisition module includes:

[0068] The desired signal and actual output signal acquisition sub-module is used to acquire the desired signal and the actual output signal through the adaptive filter;

[0069] The error signal acquisition sub-module is used to determine the error signal according to the desired signal and the actual output signal when the adaptive filter acquires the desired signal and the actual output signal.

[0070] Optionally, the re-driver includes a storage control module, wherein the storage control module establishes a communication connection with the adaptive filter;

[0071] The desired signal and actual output signal acquisition sub-module includes:

[0072] The initial signal acquisition unit is used to acquire the initial signal through the storage control module;

[0073] The desired signal sending unit is used to use the initial signal as the desired signal and send the desired signal to the adaptive filter when the storage control module acquires the initial signal.

[0074] Optionally, the desired signal and actual output signal acquisition sub-module includes:

[0075] The attenuation signal acquisition unit is used to acquire the attenuation signal and the weight coefficient of the adaptive filter through the adaptive filter, wherein the attenuation signal is formed by the attenuation of the desired signal during the transmission in the signal transmission path;

[0076] A convolution processing unit, configured to perform convolution processing on the attenuation signal and the weight coefficients of the adaptive filter when the adaptive filter obtains the attenuation signal and the weight coefficients of the adaptive filter, so as to obtain an actual output signal.

[0077] Optionally, the square expected value judgment sub-module of the error signal includes:

[0078] A next square expected value acquisition unit of the error signal, configured to repeatedly execute the steps of obtaining an error signal through the adaptive filter, determining a square value of the error signal according to the error signal, and determining a square expected value of the error signal according to the square value of the error signal, so as to obtain a next square expected value of the error signal;

[0079] A first square expected value judgment unit of the error signal, configured to determine that the square expected value of the error signal reaches the minimum if the next square expected value of the error signal is greater than or equal to the square expected value of the error signal;

[0080] A second square expected value judgment unit of the error signal, configured to determine that the square expected value of the error signal does not reach the minimum if the next square expected value of the error signal is less than the square expected value of the error signal.

[0081] Optionally, the target weight coefficient determination module includes:

[0082] A second target weight coefficient determination sub-module, configured to repeatedly execute the steps of updating the weight coefficients of the adaptive filter, obtaining an error signal through the adaptive filter, determining a square value of the error signal according to the error signal, determining a square expected value of the error signal according to the square value of the error signal, and judging whether the square expected value of the error signal reaches the minimum until the square expected value of the error signal reaches the minimum, determining the weight coefficients, and using the weight coefficients as the target weight coefficients of the adaptive filter when the square expected value of the error signal does not reach the minimum.

[0083] Optionally, the second target weight coefficient determination sub-module includes:

[0084] A target gradient and convergence factor determination unit, configured to pre-determine a target gradient and a convergence factor;

[0085] A weight coefficient update unit, configured to determine new weight coefficients of the adaptive filter according to the current weight coefficients of the adaptive filter, the convergence factor, and the target gradient.

[0086] Optionally, the target gradient and convergence factor determination unit includes:

[0087] An instantaneous square value determination subunit of the error signal, configured to use the square value of any one of the error signals as the instantaneous square value of the error signal;

[0088] An approximate gradient operation subunit, configured to perform an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient;

[0089] A target gradient determination subunit, configured to use the approximate gradient as the target gradient.

[0090] Optionally, the re-driver includes a high-speed digital-to-analog converter and an output amplification stage. Among them, the high-speed digital-to-analog converter is respectively communicatively connected to the output amplification stage and the target adaptive filter. The device includes:

[0091] A data digital-to-analog conversion module, configured to send the target output signal to the high-speed digital-to-analog converter through the target adaptive filter;

[0092] An analog target output signal sending module, configured to the high-speed digital-to-analog converter perform signal conversion processing on the target output signal to obtain an analog target output signal, and send the analog target output signal to the output amplification stage;

[0093] An output amplification stage processing module, configured to the output amplification stage perform signal amplification processing on the analog target output information to obtain a processed target output signal.

[0094] According to a third aspect of the present application, there is provided a signal processing system, which includes an adaptive filter and a signal preprocessing module;

[0095] The signal preprocessing module is configured to preprocess a pre-acquired attenuation signal to be processed to obtain a digital attenuation signal, and send the digital attenuation signal to the target adaptive filter;

[0096] The adaptive filter is configured to obtain an error signal, determine a target weight coefficient of the adaptive filter according to the error signal, configure the adaptive filter according to the target weight coefficient to obtain a target adaptive filter, and perform convolution processing on the digital attenuation signal based on the target weight coefficient through the target adaptive filter to obtain a target output signal.

[0097] According to yet another aspect of the present application, there is also provided an electronic device, including:

[0098] A processor;

[0099] A memory for storing executable instructions of the processor;

[0100] Wherein, the processor is configured to execute the instructions to implement the steps of the signal processing method as described above.

[0101] According to another aspect of the present application, there is also provided a readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the signal processing method as described above are implemented.

[0102] According to another aspect of the present application, there is also provided a computer program product, including a computer program / instructions, and when the computer program / instructions are executed by a processor, the steps of the signal processing method as described above are implemented.

[0103] The signal processing method provided by the embodiments of the present application is applied to a re-driver, wherein the re-driver includes an adaptive filter; an error signal is obtained through the adaptive filter; a target weight coefficient of the adaptive filter is determined according to the error signal; the adaptive filter is configured according to the target weight coefficient to obtain a target adaptive filter; a pre-acquired attenuation signal to be processed is preprocessed to obtain a digital attenuation signal; the digital attenuation signal is sent to the target adaptive filter; through the target adaptive filter, the digital attenuation signal is convolved based on the target weight coefficient to obtain a target output signal. The present application dynamically determines the target weight coefficient according to the error signal through the adaptive filter, and configures the adaptive filter based on the target weight coefficient, realizing the automatic configuration of the re-driver parameters, improving the efficiency and accuracy of the re-driver parameter configuration, thereby improving the efficiency and accuracy of signal processing using the re-driver, and avoiding the problems of low efficiency and low accuracy of signal processing caused by repeatedly manually debugging the parameters of each key module in the re-driver.

[0104] The above description is only an overview of the technical solution of the present application. In order to be able to understand the technical means of the present application more clearly, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present application more obvious and understandable, the following specifically gives the specific implementation manners of the present application. Description of the Drawings

[0105] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art.

[0106] Figure 1 It is a schematic structural diagram of a Redriver chip provided by an embodiment of the present application;

[0107] Figure 2 It is a schematic structural diagram of an improved Redriver chip provided by an embodiment of the present application;

[0108] Figure 3It is one of the step flowcharts of a signal processing method provided by an embodiment of the present application;

[0109] Figure 4 It is the second of the step flowcharts of a signal processing method provided by an embodiment of the present application;

[0110] Figure 5 It is the third of the step flowcharts of a signal processing method provided by an embodiment of the present application;

[0111] Figure 6 It is the fourth of the step flowcharts of a signal processing method provided by an embodiment of the present application;

[0112] Figure 7 It is the fifth of the step flowcharts of a signal processing method provided by an embodiment of the present application;

[0113] Figure 8 It is the block diagram of a signal processing device provided by an embodiment of the present application;

[0114] Figure 9 It is the schematic diagram of an electronic device provided by an embodiment of the present application. Detailed implementation manners

[0115] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will elaborate on each implementation manner of the present application in conjunction with the accompanying drawings. However, those of ordinary skill in the art can understand that in each implementation manner of the present application, many technical details are proposed for the convenience of readers to understand the present application. However, even without these technical details and various changes and modifications based on the following implementation manners, the technical solutions required to be protected by the present application can still be achieved. The division of the following embodiments is for convenience of description and should not constitute any limitation on the specific implementation manner of the present application. The various embodiments can be combined and cross-referenced with each other on the premise of not being contradictory.

[0116] It should be noted that in the embodiments of the present application, the re-driver can be a Redriver chip, which is mainly used to enhance the amplitude of the signal and assist the signal to be transmitted over a longer distance.

[0117] The structural schematic diagram of the existing Redriver chip is as Figure 1As shown in the figure, the parameter configuration process of the Redriver chip mainly relies on manual configuration, including manually configuring the fixed gain values of each frequency band in the equalizer, manually configuring the fixed gain values of the specified frequency band in the linear amplifier, and manually configuring the fixed swing upper limit in the buffer. After completing the configuration of the Redriver chip parameters, it is necessary to repeatedly manually debug the parameters of the equalizer, linear amplifier, and buffer in the Redrvier chip by testing the signal quality at the end of the post-transmission path until the signal conditioning effect that meets the requirements is achieved. However, the operation process of this method is very cumbersome and cannot guarantee that the signal debugging effect is always ideal and stable. Moreover, the subjectivity of manually debugging parameters is relatively strong, making it difficult to achieve precise parameter adjustment, which affects the efficiency and quality of signal processing. Therefore, the existing method of using the Redriver chip to process signals has problems of low signal processing efficiency and low accuracy.

[0118] To solve the problems of low signal processing efficiency and low accuracy in the method of using the Redriver chip to process signals, the embodiment of this application has improved the structure of the Redriver chip. Specifically, the equalizer, linear amplifier, and buffer in the Redriver chip are cancelled, and a high-speed analog-to-digital converter, an adaptive filter, a high-speed digital-to-analog converter, and a storage control module are added. The schematic diagram of the improved structure of the Redriver chip is as Figure 2 shown.

[0119] After completing the improvement of the Redriver chip structure, the adaptive filter dynamically determines a relatively ideal weight coefficient of the adaptive filter, that is, the target weight coefficient, according to the error signal. Subsequently, this set of target weight coefficients of the adaptive filter can be used as the fixed configuration parameters of the Redriver chip. Then, the Redriver chip configured with the target weight coefficients filters and amplifies all unknown random signals under the same transmission path loss, and finally realizes the signal conditioning and driving functions of the Redriver chip, thereby realizing the automatic configuration of the Redriver chip parameters, improving the efficiency and accuracy of the Redriver chip parameter configuration, and thus improving the efficiency and accuracy of using the Redriver chip for signal processing, avoiding the problems of low signal processing efficiency and low accuracy caused by repeatedly manually debugging the parameters of the equalizer, linear amplifier, and buffer in the Redriver chip.

[0120] Referring to Figure 3 , a flowchart of steps of a signal processing method provided by an embodiment of this application is shown, which is applied to a re-driver. The re-driver includes an adaptive filter, and the method may include:

[0121] Step 301, obtaining an error signal through the adaptive filter.

[0122] Step 302: Determine the target weight coefficient of the adaptive filter according to the error signal.

[0123] Step 303: Configure the adaptive filter according to the target weight coefficient to obtain the target adaptive filter.

[0124] It should be noted that in the embodiments of the present application, in order to determine the target weight coefficient of the adaptive filter, the error signal can be obtained in advance through the adaptive filter. When the adaptive filter obtains the error signal, the target weight coefficient of the adaptive filter is determined based on the error signal. After determining the target weight coefficient of the adaptive filter, the adaptive filter is configured based on the target weight coefficient of the adaptive filter to obtain the target adaptive filter. Subsequently, all unknown random signals under the same transmission path loss can be filtered and amplified through the target adaptive filter, and finally the signal conditioning and driving functions of the Redriver chip can be realized.

[0125] Step 304: Preprocess the pre-obtained attenuation signal to be processed to obtain a digital attenuation signal.

[0126] Step 305: Send the digital attenuation signal to the target adaptive filter.

[0127] Step 306: Through the target adaptive filter, perform convolution processing on the digital attenuation signal based on the target weight coefficient to obtain a target output signal.

[0128] It should be noted that in the embodiments of the present application, attenuation will occur during the signal transmission process of the original signal in the pre-transmission path of the Redriver chip. The signal formed after attenuation is the attenuation signal to be processed. The attenuation signal to be processed will pass through the Redriver chip, and the Redriver chip will perform signal conditioning on the attenuation signal to be processed, so that the output signal of the Redriver chip can approximate the original signal.

[0129] When the Redriver chip receives the attenuation signal to be processed, it preprocesses the attenuation signal to be processed through the input buffer stage and the high-speed analog-to-digital converter respectively. The preprocessed attenuation signal to be processed is the digital attenuation signal. After obtaining the digital attenuation signal, the digital attenuation signal is sent to the target adaptive filter. When the target adaptive filter receives the digital attenuation signal, it performs a convolution operation on the target weight coefficient and the digital attenuation signal to obtain a target output signal.

[0130] In this application, an adaptive filter dynamically determines target weight coefficients according to an error signal, and configures the adaptive filter based on the target weight coefficients, thereby realizing the automatic configuration of the parameters of the heavy driver, improving the efficiency and accuracy of the parameter configuration of the heavy driver, and thus improving the efficiency and accuracy of signal processing using the heavy driver, and avoiding the problems of low efficiency and low accuracy of signal processing caused by repeatedly manually debugging the parameters of each key module in the heavy driver.

[0131] Further, in the embodiment of this application, step 304 may further include the following steps:

[0132] The input buffer stage preliminarily filters the attenuation signal to be processed to obtain a filtered attenuation signal.

[0133] When the filtered attenuation signal is obtained, the input buffer stage sends the filtered attenuation signal to the high-speed analog-to-digital converter.

[0134] When the high-speed analog-to-digital converter receives the filtered attenuation signal, it performs signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal.

[0135] It should be noted that in the embodiment of this application, the specific implementation process of preprocessing the pre-obtained attenuation signal to be processed to obtain a digital attenuation signal is as follows: The attenuation signal to be processed first passes through the input buffer stage, and the input buffer stage preliminarily filters obvious noises and the like in the attenuation signal to be processed. The attenuation signal to be processed after preliminary filtering is the filtered attenuation signal.

[0136] The original signal is an analog signal. The attenuation signal to be processed obtained after the original signal is attenuated is an analog signal. The filtered attenuation signal obtained after the attenuation signal to be processed is preliminarily filtered by the input buffer stage is an analog signal. When the input buffer stage obtains the filtered attenuation signal, it sends the filtered attenuation signal to the high-speed analog-to-digital converter. When the high-speed analog-to-digital converter receives the filtered attenuation signal sent by the input buffer stage, it performs analog-to-digital conversion on the filtered attenuation signal to obtain a digital attenuation signal.

[0137] In this application, the input buffer stage preliminarily filters the attenuation signal to be processed, which can effectively remove the noise in the attenuation signal to be processed and improve the clarity and accuracy of the attenuation signal to be processed. In addition, in this application, the high-speed analog-to-digital converter performs analog-to-digital conversion on the attenuation signal to be processed after preliminary filtering, ensuring that the attenuation signal to be processed after preliminary filtering can be used for more complex signal processing and analysis, providing a reliable data basis for subsequent signal processing.

[0138] Further, as Figure 4As shown, FIG. 2 shows the second flowchart of the steps of the signal processing method provided by the embodiment of the present application. In the embodiment of the present application, step 302 may further include the following steps:

[0139] Step 401, determining the square value of the error signal according to the error signal.

[0140] Step 402, determining the expected square value of the error signal according to the square value of the error signal.

[0141] Step 403, judging whether the expected square value of the error signal reaches the minimum according to the expected square value of the error signal and the previously obtained expected square value of the next error signal.

[0142] Step 404, when the expected square value of the error signal reaches the minimum, determining the weight coefficient and using the weight coefficient as the target weight coefficient of the adaptive filter.

[0143] It should be noted that, in the embodiment of the present application, when the error signal is obtained by the adaptive filter in advance, the adaptive filter determines the square value of the error signal according to the error signal, where the error signal can be represented by and the square value of the error signal can be represented as . When the adaptive filter determines the square value of the error signal, the adaptive filter determines the expected square value of the error signal according to the square value of the error signal, where the expected square value of the error signal can be represented as E .

[0144] When the adaptive filter determines the expected square value of the error signal, it can judge whether the current expected square value of the error signal reaches the minimum according to the current expected square value of the error signal and the previously obtained expected square value of the next error signal.

[0145] If the current expected square value of the error signal reaches the minimum, determine the weight coefficient and use the weight coefficient as the target weight coefficient of the adaptive filter.

[0146] In the present application, when the expected square value of the error signal reaches the minimum, the weight coefficient is determined and the weight coefficient is used as the target weight coefficient of the adaptive filter, ensuring that the target weight coefficient can make the performance of the adaptive filter reach the best and optimizing the performance of the adaptive filter.

[0147] Further, in the embodiment of the present application, step 301 may further include the following steps:

[0148] Obtain the desired signal and the actual output signal through the adaptive filter.

[0149] When the adaptive filter obtains the desired signal and the actual output signal, the error signal is determined according to the desired signal and the actual output signal.

[0150] It should be noted that in the embodiment of the present application, the specific implementation process of obtaining the error signal through the adaptive filter in advance is as follows: the desired signal is obtained in advance through the adaptive filter and the desired signal is determined in advance through the adaptive filter; when the adaptive filter obtains the desired signal and the actual output signal, the desired signal and the actual output signal are substituted into formula (1), and the error signal can be obtained.

[0151] Formula (1)

[0152] Wherein, is the error signal, is the desired signal, is the actual output signal.

[0153] In the present application, the error signal is determined according to the desired signal and the actual output signal through the adaptive filter, and then the error signal can be used as feedback to guide the adaptive adjustment of the adaptive filter, thereby improving the accuracy, real-time performance and system stability of the adaptive filter, optimizing the resource allocation, and having wide application value.

[0154] Furthermore, in the embodiment of the present application, the step of "obtaining the desired signal through the adaptive filter" may further include the following steps:

[0155] Obtain the initial signal through the storage control module.

[0156] When the storage control module obtains the initial signal, the initial signal is used as the desired signal and the desired signal is sent to the adaptive filter.

[0157] It should be noted that in the embodiment of the present application, the initial signal is a signal that has not been transmitted through the pre-transmission path of the Redriver chip.

[0158] The initial signal is loaded into the storage control module in advance. After the initial signal is loaded into the storage control module, the initial signal is stored by the storage control module and the initial signal is sent to the adaptive filter as the desired signal. The adaptive filter can perform adaptive training according to the attenuation signal and the desired signal to obtain the required relatively ideal weight coefficient of the adaptive filter, that is, the target weight coefficient of the adaptive filter. Among them, the attenuation signal is formed by the attenuation of the desired signal during the transmission in the signal transmission path.

[0159] The present application obtains an initial signal through a storage control module and sends the initial signal as a desired signal to an adaptive filter, enabling the adaptive filter to perform adaptive training based on the attenuated signal (i.e., the desired signal that has attenuated during transmission) and the desired signal, and minimizing the error by adjusting the weight coefficients, thereby obtaining the target weight coefficients of the required adaptive filter.

[0160] Further, in the embodiment of the present application, the step of "obtaining the actual output signal through the adaptive filter" may further include the following steps:

[0161] Obtain the attenuated signal and the weight coefficients of the adaptive filter through the adaptive filter, where the attenuated signal is formed by the attenuation of the desired signal during the transmission in the signal transmission path.

[0162] When the adaptive filter obtains the attenuated signal and the weight coefficients of the adaptive filter, perform a convolution process on the attenuated signal and the weight coefficients of the adaptive filter to obtain the actual output signal.

[0163] It should be noted that in the embodiment of the present application, a number of attenuated signals are pre-constructed, and the number of attenuated signals can be expressed as , where X(n) is the number of attenuated signals, L is the length of the adaptive filter, that is, the adaptive filter can process L attenuated signals, n is the number of sampling points, and T is the transpose.

[0164] Pre-construct a number of weight coefficients of the adaptive filter, and the number of weight coefficients of the adaptive filter can be expressed as , where W(n) is the number of weight coefficients of the adaptive filter, L is the length of the adaptive filter, n is the number of sampling points, and T is the transpose.

[0165] Obtain the attenuated signal from a number of attenuated signals and obtain the weight coefficients of the adaptive filter from a number of weight coefficients of the adaptive filter. When the adaptive filter obtains the attenuated signal and the weight coefficients of the adaptive filter, perform a convolution operation on the attenuated signal and the weight coefficients of the adaptive filter to obtain the actual output signal.

[0166] The present application performs a convolution operation on the attenuated signal and the weight coefficients of the adaptive filter through the adaptive filter, enabling the adaptive filter to compensate for the attenuated signal using the weight coefficients, thereby restoring the original state of the signal and improving the signal recovery ability.

[0167] Further, as Figure 5 shown, FIG. 3 shows the flowchart of the steps of the signal processing method provided by the embodiment of the present application. In the embodiment of the present application, step 403 may further include the following steps:

[0168] Step 501: Repeatedly execute the steps of obtaining an error signal through an adaptive filter, determining the squared value of the error signal based on the error signal, and determining the expected squared value of the error signal based on the squared value of the error signal to obtain the next expected squared value of the error signal.

[0169] Step 502: If the next expected squared value of the error signal is greater than or equal to the expected squared value of the error signal, it is determined that the expected squared value of the error signal reaches the minimum.

[0170] Step 503: If the next expected squared value of the error signal is less than the expected squared value of the error signal, it is determined that the expected squared value of the error signal does not reach the minimum.

[0171] It should be noted that in the embodiment of the present application, the specific implementation process of determining whether the expected squared value of the error signal reaches the minimum according to the expected squared value of the error signal and the previously obtained next expected squared value of the error signal is as follows: Repeatedly execute the steps of obtaining an error signal through an adaptive filter, determining the squared value of the error signal based on the error signal, and determining the expected squared value of the error signal based on the squared value of the error signal to obtain the next expected squared value of the error signal.

[0172] Compare the current expected squared value of the error signal with the next expected squared value of the error signal. If the next expected squared value of the error signal is greater than or equal to the expected squared value of the error signal, it is determined that the current expected squared value of the error signal reaches the minimum. If the next expected squared value of the error signal is less than the current expected squared value of the error signal, it is determined that the current expected squared value of the error signal does not reach the minimum.

[0173] For example: If the current desired signal is , and the current actual output signal is , then the current error signal is , and the current expected squared value of the error signal is E ; If the next desired signal is , and the next actual output signal is , then the next error signal is , and the next expected squared value of the error signal is E . If E is greater than or equal to E , it is determined that the value of E has reached the minimum. If E is less than E , it is determined that the value of E does not reach the minimum.

[0174] In this application, by iteratively comparing the expected value of the square of the error signal, the adaptive filter can quickly detect the convergence point, thereby accelerating the adjustment speed of the weight coefficients and improving the acquisition efficiency of the target weight coefficients.

[0175] Further, in the embodiment of this application, after step 403, the following steps may further be included:

[0176] In the case where the expected value of the square of the error signal has not reached the minimum, repeatedly execute the steps of updating the weight coefficients of the adaptive filter, obtaining the error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the expected value of the square of the error signal according to the square value of the error signal, and judging whether the expected value of the square of the error signal has reached the minimum, until the expected value of the square of the error signal reaches the minimum, determining the weight coefficients, and using the weight coefficients as the target weight coefficients of the adaptive filter.

[0177] It should be noted that, in the embodiment of this application, if the expected value of the square of the current error signal has not reached the minimum, then repeatedly execute the steps of updating the weight coefficients of the adaptive filter, re-obtaining the error signal, determining the square value of the error signal, determining the expected value of the square of the error signal, and judging whether the expected value of the square of the error signal has reached the minimum, until the expected value of the square of the error signal reaches the minimum, obtaining the weight coefficients at this time, and using the weight coefficients at this time as the target weight coefficients of the adaptive filter.

[0178] Among them, in the process of re-obtaining the error signal, re-obtaining the attenuation signal is involved. If the current error signal is , then the re-obtained attenuation signal is , ; if the current error signal is , , then the re-obtained attenuation signal is , , , and so on for iteration.

[0179] In this application, in the case where the expected value of the square of the error signal has not reached the minimum, the adaptive filter can more precisely adjust the weight coefficients through continuous iterative updating of the weight coefficients to minimize the expected value of the square of the error signal and improve the performance of the adaptive filter.

[0180] Further, in the embodiment of this application, the step of "updating the weight coefficients of the adaptive filter" may further include the following steps:

[0181] Predetermine the target gradient and the convergence factor.

[0182] Determine the weight coefficients of the new adaptive filter according to the weight coefficients, convergence factor, and target gradient of the current adaptive filter.

[0183] It should be noted that, in the embodiments of the present application, the mean square value of the error signal is minimized by the gradient descent method. The basic principle of the gradient descent method is to update the weight coefficients of the adaptive filter along the gradient direction of the mean square value of the error signal until the minimum value of the mean square value of the error signal is reached.

[0184] The target gradient and the convergence factor need to be determined in advance. When the target gradient and the convergence factor are determined, substituting the weight coefficients, convergence factor, and target gradient of the current adaptive filter into formula (2), the weight coefficients of the new adaptive filter can be obtained.

[0185] W(n + 1)=W(n)+u[- Formula (2)

[0186] where W(n + 1) is the weight coefficient of the new adaptive filter, W(n) is the weight coefficient of the current adaptive filter, u is the convergence factor, is the target gradient, where the convergence factor is a constant that controls the adjustment amplitude of the weight coefficients of the adaptive filter.

[0187] Furthermore, as Figure 6 shown, Figure 4 shows the flowchart of the signal processing method provided by the embodiments of the present application. In the embodiments of the present application, the step of "determining the target gradient in advance" may further include the following steps:

[0188] Step 601, take the square value of any error signal as the instantaneous square value of the error signal.

[0189] Step 602, perform an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient.

[0190] Step 603, take the approximate gradient as the target gradient.

[0191] It should be noted that, in the embodiments of the present application, since accurately calculating the target gradient requires a large amount of time and effort, there is a problem of low calculation efficiency of the target gradient. To solve the problem of low calculation efficiency of the target gradient, in the embodiments of the present application, the square value of any error signal can be taken as the instantaneous square value of the error signal, and an approximate gradient operation is performed on the instantaneous square value of the error signal to obtain an approximate gradient. The specific calculation process of performing an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient is shown in formula (3).

[0192] Formula (3)

[0193] Among them, is the approximate gradient, is the square value of the error signal, is the weight coefficient of the current adaptive filter, is the error signal, is the desired signal, is the attenuation signal.

[0194] After the adaptive filter obtains the approximate gradient, the approximate gradient is used as the target gradient. After obtaining the target gradient, substituting the target gradient into formula (2), the final iterative formula for the weight coefficient of the new adaptive filter can be obtained, as shown in formula (4).

[0195] W(n + 1)=W(n)+2ue(n)X(n) Formula (4)

[0196] Among them, W(n + 1) is the weight coefficient of the new adaptive filter, W(n) is the weight coefficient of the current adaptive filter, u is the convergence factor, is the current error signal, is the current attenuation signal.

[0197] This application can quickly approach the minimum value and improve the convergence speed by using the gradient descent method to update the weight coefficient along the gradient direction of the square expected value of the error signal. In addition, this application performs an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient and uses the approximate gradient as the target gradient, which can reduce the large amount of time and effort required to calculate the target gradient and improve the efficiency of target gradient calculation.

[0198] Furthermore, as Figure 7 shown, it shows the fifth step flowchart of the signal processing method provided by the embodiment of this application. In the embodiment of this application, the method may further include the following steps:

[0199] Step 701, sending the target output signal to the high-speed digital-to-analog converter through the target adaptive filter.

[0200] Step 702, the high-speed digital-to-analog converter performs signal conversion processing on the target output signal to obtain an analog target output signal and sends the analog target output signal to the output amplification stage.

[0201] Step 703, the output amplification stage performs signal amplification processing on the analog target output information to obtain the processed target output signal.

[0202] It should be noted that in the embodiments of the present application, after the target adaptive filter obtains the target output signal, the target output signal is sent to a high-speed digital-to-analog converter. When the high-speed digital-to-analog converter receives the target output signal, it performs digital-to-analog conversion on the target output signal to obtain an analog target output signal, and sends the analog target output signal to the output amplification stage. When the output amplification stage receives the analog target output signal sent by the high-speed digital-to-analog converter, it performs signal amplification processing on the analog target output information to obtain the processed target output signal.

[0203] In the present application, the high-speed digital-to-analog converter performs digital-to-analog conversion on the target output signal, ensuring that the signal is not distorted during the conversion process from the digital domain to the analog domain, and optimizing the signal transmission effect. In addition, in the present application, the output amplification stage performs amplification processing on the target output signal, enhancing the signal strength, enabling the signal to be transmitted over longer distances and in more complex environments, and improving the signal coverage range and transmission efficiency.

[0204] Further, in the embodiments of the present application, after step 403, the following steps may further be included:

[0205] In the case where the mean square value of the error signal has not reached the minimum, repeatedly execute the steps of updating the convergence factor of the adaptive filter, obtaining the error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the mean square value of the error signal according to the square value of the error signal, and determining whether the mean square value of the error signal has reached the minimum, until the mean square value of the error signal reaches the minimum, determining the weight coefficient, and using the weight coefficient as the target weight coefficient of the adaptive filter.

[0206] It should be noted that in the embodiments of the present application, if the mean square value of the current error signal has not reached the minimum, then repeatedly execute the steps of updating the convergence factor of the adaptive filter, re-obtaining the error signal, determining the square value of the error signal, determining the mean square value of the error signal, and determining whether the mean square value of the error signal has reached the minimum, until the mean square value of the error signal reaches the minimum, obtaining the weight coefficient at this time, and using the weight coefficient at this time as the target weight coefficient of the adaptive filter.

[0207] In the present application, in the case where the mean square value of the error signal has not reached the minimum, the adaptive filter can more precisely adjust the adjustment amplitude of the weight coefficient through continuous iterative update of the convergence factor to minimize the mean square value of the error signal and improve the performance of the adaptive filter.

[0208] According to the embodiments of the present application, a signal processing device is further provided. Refer to Figure 8 , Figure 8It is a block diagram of a signal processing device provided by an embodiment of the present application. The signal processing device includes:

[0209] An error signal acquisition module 801, configured to acquire an error signal through an adaptive filter;

[0210] A target weight coefficient determination module 802, configured to determine a target weight coefficient of the adaptive filter according to the error signal;

[0211] An adaptive filter configuration module 803, configured to configure the adaptive filter according to the target weight coefficient to obtain a target adaptive filter;

[0212] A data preprocessing module 804, configured to preprocess a to-be-processed attenuation signal acquired in advance to obtain a digital attenuation signal;

[0213] A data sending module 805, configured to send the digital attenuation signal to the target adaptive filter;

[0214] A target adaptive filter processing module 806, configured to perform convolution processing on the digital attenuation signal based on the target weight coefficient through the target adaptive filter to obtain a target output signal.

[0215] Optionally, the re-driver includes an input buffer stage and a high-speed analog-to-digital converter, wherein the input buffer stage and the high-speed analog-to-digital converter establish a communication connection;

[0216] The data preprocessing module includes:

[0217] An input buffer stage processing sub-module, configured to perform preliminary filtering on the to-be-processed attenuation signal through the input buffer stage to obtain a filtered attenuation signal;

[0218] A filtered attenuation signal sending sub-module, configured to send the filtered attenuation signal to the high-speed analog-to-digital converter through the input buffer stage when the filtered attenuation signal is obtained;

[0219] A data analog-to-digital conversion sub-module, configured to perform signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal when the high-speed analog-to-digital converter receives the filtered attenuation signal.

[0220] Optionally, the target weight coefficient determination module includes:

[0221] An error signal square value determination sub-module, configured to determine a square value of the error signal according to the error signal;

[0222] An error signal square expected value determination sub-module, configured to determine an expected square value of the error signal according to the square value of the error signal;

[0223] The squared expected value judgment sub-module of the error signal is used to judge whether the squared expected value of the error signal reaches the minimum according to the squared expected value of the error signal and the pre-obtained squared expected value of the next error signal;

[0224] The first target weight coefficient determination sub-module is used to determine the weight coefficient when the squared expected value of the error signal reaches the minimum, and use the weight coefficient as the target weight coefficient of the adaptive filter.

[0225] Optionally, the error signal acquisition module includes:

[0226] The desired signal and actual output signal acquisition sub-module is used to obtain the desired signal and the actual output signal through the adaptive filter;

[0227] The error signal acquisition sub-module is used to determine the error signal according to the desired signal and the actual output signal when the adaptive filter obtains the desired signal and the actual output signal.

[0228] Optionally, the re-driver includes a storage control module, wherein the storage control module establishes a communication connection with the adaptive filter;

[0229] The desired signal and actual output signal acquisition sub-module includes:

[0230] The initial signal acquisition unit is used to obtain the initial signal through the storage control module;

[0231] The desired signal sending unit is used to use the initial signal as the desired signal and send the desired signal to the adaptive filter when the storage control module obtains the initial signal.

[0232] Optionally, the desired signal and actual output signal acquisition sub-module includes:

[0233] The attenuation signal acquisition unit is used to obtain the attenuation signal and the weight coefficient of the adaptive filter through the adaptive filter, wherein the attenuation signal is formed by the attenuation of the desired signal during the transmission in the signal transmission path;

[0234] The convolution processing unit is used to perform convolution processing on the attenuation signal and the weight coefficient of the adaptive filter to obtain the actual output signal when the adaptive filter obtains the attenuation signal and the weight coefficient of the adaptive filter.

[0235] Optionally, the squared expected value judgment sub-module of the error signal includes:

[0236] The square expected value acquisition unit of the next error signal is configured to repeatedly execute the steps of obtaining an error signal through an adaptive filter, determining the square value of the error signal according to the error signal, and determining the square expected value of the error signal according to the square value of the error signal, so as to obtain the square expected value of the next error signal;

[0237] The first square expected value determination unit of the error signal is configured to determine that the square expected value of the error signal reaches the minimum if the square expected value of the next error signal is greater than or equal to the square expected value of the error signal;

[0238] The second square expected value determination unit of the error signal is configured to determine that the square expected value of the error signal does not reach the minimum if the square expected value of the next error signal is less than the square expected value of the error signal.

[0239] Optionally, the target weight coefficient determination module includes:

[0240] The second target weight coefficient determination sub-module is configured to, when the square expected value of the error signal does not reach the minimum, repeatedly execute the steps of updating the weight coefficient of the adaptive filter, obtaining an error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the square expected value of the error signal according to the square value of the error signal, and determining whether the square expected value of the error signal reaches the minimum, until the square expected value of the error signal reaches the minimum, determining the weight coefficient, and using the weight coefficient as the target weight coefficient of the adaptive filter.

[0241] Optionally, the second target weight coefficient determination sub-module includes:

[0242] The target gradient and convergence factor determination unit is configured to pre-determine the target gradient and the convergence factor;

[0243] The weight coefficient update unit is configured to determine the weight coefficient of the new adaptive filter according to the weight coefficient of the current adaptive filter, the convergence factor, and the target gradient.

[0244] Optionally, the target gradient and convergence factor determination unit includes:

[0245] The instantaneous square value determination sub-unit of the error signal is configured to use the square value of any error signal as the instantaneous square value of the error signal;

[0246] The approximate gradient operation sub-unit is configured to perform an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient;

[0247] The target gradient determination sub-unit is configured to use the approximate gradient as the target gradient.

[0248] Optionally, the redriver includes a high-speed digital-to-analog converter and an output amplification stage. The high-speed digital-to-analog converter is communicatively connected to the output amplification stage and the target adaptive filter respectively. The apparatus includes:

[0249] A data digital-to-analog conversion module, configured to send a target output signal to the high-speed digital-to-analog converter through the target adaptive filter;

[0250] An analog target output signal sending module, configured to enable the high-speed digital-to-analog converter to perform signal conversion processing on the target output signal to obtain an analog target output signal, and send the analog target output signal to the output amplification stage;

[0251] An output amplification stage processing module, configured to enable the output amplification stage to perform signal amplification processing on the analog target output information to obtain a processed target output signal.

[0252] According to an embodiment of the present application, a signal processing system is further provided. The signal processing system includes an adaptive filter and a signal preprocessing module.

[0253] The signal preprocessing module is configured to preprocess a to-be-processed attenuation signal obtained in advance to obtain a digital attenuation signal, and send the digital attenuation signal to the target adaptive filter.

[0254] The adaptive filter is configured to obtain an error signal, determine a target weight coefficient of the adaptive filter according to the error signal, configure the adaptive filter according to the target weight coefficient to obtain a target adaptive filter, and perform convolution processing on the digital attenuation signal based on the target weight coefficient through the target adaptive filter to obtain a target output signal.

[0255] It should be noted that, in the embodiment of the present application, in order to determine the target weight coefficient of the adaptive filter, an error signal can be obtained in advance through the adaptive filter. When the adaptive filter obtains the error signal, the target weight coefficient of the adaptive filter is determined based on the error signal. When the target weight coefficient of the adaptive filter is determined, the adaptive filter is configured according to the target weight coefficient of the adaptive filter to obtain a target adaptive filter. Subsequently, all unknown random signals under the same transmission path loss can be filtered and amplified through the target adaptive filter, and finally the signal conditioning and driving functions of the Redriver chip can be realized.

[0256] During the process of signal transmission of the original signal in the front-end transmission path of the Redriver chip, attenuation will occur. The signal formed after attenuation is the to-be-processed attenuation signal. The to-be-processed attenuation signal will pass through the Redriver chip, and the Redriver chip will perform signal conditioning on the to-be-processed attenuation signal, so that the output signal of the Redriver chip can approximate the original signal.

[0257] When the Redriver chip receives the attenuation signal to be processed, it preprocesses the attenuation signal to be processed through an input buffer stage and a high-speed analog-to-digital converter respectively. The attenuation signal to be processed after preprocessing is the digital attenuation signal. When the digital attenuation signal is obtained, the digital attenuation signal is sent to the target adaptive filter. When the target adaptive filter receives the digital attenuation signal, it performs a convolution operation on the target weight coefficient and the digital attenuation signal to obtain the target output signal.

[0258] In this application, the adaptive filter dynamically determines the target weight coefficient according to the error signal, and configures the adaptive filter based on the target weight coefficient, realizing the automatic configuration of the Redriver parameters, improving the efficiency and accuracy of the Redriver parameter configuration, thereby improving the efficiency and accuracy of signal processing using the Redriver, and avoiding the problems of low efficiency and low accuracy of signal processing caused by repeatedly manually debugging the parameters of each key module in the Redriver.

[0259] An embodiment of this application also provides an electronic device, as Figure 9 shown, including a processor 901, a communication interface 902, a memory 903, and a communication bus 904. Among them, the processor 901, the communication interface 902, and the memory 903 complete communication with each other through the communication bus 904.

[0260] The memory 903 is used to store computer programs.

[0261] When the processor 901 executes the program stored on the memory 903, the following steps are implemented:

[0262] Obtain an error signal through the adaptive filter;

[0263] Determine the target weight coefficient of the adaptive filter according to the error signal;

[0264] Configure the adaptive filter according to the target weight coefficient to obtain the target adaptive filter;

[0265] Preprocess the pre-obtained attenuation signal to be processed to obtain a digital attenuation signal;

[0266] Send the digital attenuation signal to the target adaptive filter;

[0267] Through the target adaptive filter, perform convolution processing on the digital attenuation signal based on the target weight coefficient to obtain the target output signal.

[0268] The communication bus mentioned in the above terminal may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. This communication bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of convenience of representation, only a thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0269] The communication interface is used for communication between the above terminal and other devices.

[0270] The memory may include a Random Access Memory (RAM), or may also include a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located far from the aforementioned processor.

[0271] The above-mentioned processor may be a general-purpose processor, including a Central Processing Unit (CPU), a Network Processor (NP), etc.; it may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field-Programmable Gate Array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0272] In another embodiment provided by this application, a computer-readable storage medium is also provided. Instructions are stored in this computer-readable storage medium. When it runs on a computer, it causes the computer to execute the signal processing method described in any one of the above embodiments.

[0273] In another embodiment provided by this application, a computer program product is also provided, including a computer program / instructions. When the computer program / instructions are executed by a processor, the steps of the signal processing method described in any one of the above embodiments are implemented.

[0274] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (such as infrared, wireless, microwave, etc.) means. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that includes one or more integrated available media. The available medium can be a magnetic medium (such as a floppy disk, a hard disk, a magnetic tape), an optical medium (such as a DVD), or a semiconductor medium (such as a solid state disk (SSD)).

[0275] It should be noted that, in this document, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.

[0276] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0277] The above are only the preferred embodiments of the present application and are not intended to limit the protection scope of the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present application are all included in the protection scope of the present application.

Claims

1. A signal processing method, characterized in that: The invention is applied to a redriver, wherein the redriver comprises an adaptive filter, an input buffer stage, a high-speed analog-to-digital converter, a high-speed digital-to-analog converter and an output amplifier stage, wherein the input buffer stage establishes a communication connection with the high-speed analog-to-digital converter, and the high-speed digital-to-analog converter establishes a communication connection with the output amplifier stage and the adaptive filter respectively, and the method comprises: Acquire a desired signal through the adaptive filter; Acquiring an attenuation signal and a weight coefficient of the adaptive filter through the adaptive filter, wherein the attenuation signal is formed by attenuation of the desired signal during transmission in a signal transmission path; When the adaptive filter obtains the attenuation signal and the weight coefficient of the adaptive filter, convolution processing is performed on the attenuation signal and the weight coefficient of the adaptive filter to obtain an actual output signal; When the adaptive filter obtains the expected signal and the actual output signal, determining an error signal according to the expected signal and the actual output signal; determining a square value of the error signal according to the error signal; Determining a square expected value of the error signal according to the square value of the error signal; Repeating the steps of acquiring an error signal through the adaptive filter, determining a square value of the error signal according to the error signal, and determining a square expected value of the error signal according to the square value of the error signal, to acquire a next square expected value of the error signal; If the square expected value of the next error signal is greater than or equal to the square expected value of the error signal, determining that the square expected value of the error signal reaches a minimum; If the square expected value of the next error signal is less than the square expected value of the error signal, determining that the square expected value of the error signal has not reached a minimum; In the case that the square expected value of the error signal has not reached the minimum, the steps of predetermining the target gradient and the convergence factor, determining a new weight coefficient of the adaptive filter according to the current weight coefficient of the adaptive filter, the convergence factor and the target gradient, acquiring the error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the square expected value of the error signal according to the square value of the error signal, and judging whether the square expected value of the error signal has reached the minimum, until the square expected value of the error signal has reached the minimum, determining the weight coefficient, and using the weight coefficient as the target weight coefficient of the adaptive filter; or, Repeat the steps of updating the convergence factor of the adaptive filter, obtaining the error signal through the adaptive filter, determining the square value of the error signal according to the error signal, determining the square expected value of the error signal according to the square value of the error signal, and judging whether the square expected value of the error signal reaches a minimum, until the square expected value of the error signal reaches a minimum, determining a weight coefficient, and using the weight coefficient as a target weight coefficient of the adaptive filter; Configuring the adaptive filter according to the target weight coefficient to obtain a target adaptive filter; Performing preliminary filtering on the attenuated signal to be processed through the input buffer stage to obtain a filtered attenuated signal; In the case of obtaining the filtered attenuated signal, sending the filtered attenuated signal to the high-speed analog-to-digital converter through the input buffer stage; When the high-speed analog-to-digital converter receives the filtered attenuation signal, performing signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal; sending the digital attenuation signal to the target adaptive filter; By using the target adaptive filter, the digital attenuation signal is convolved based on the target weight coefficient to obtain a target output signal; sending the target output signal to the high-speed digital-to-analog converter through the target adaptive filter; The high-speed digital-to-analog converter performs signal conversion processing on the target output signal to obtain an analog target output signal, and sends the analog target output signal to the output amplifier stage; The output amplifier stage performs signal amplification processing on the analog target output information to obtain a processed target output signal.

2. The method according to claim 1, characterized in that After the step of determining that the square expected value of the error signal has not reached a minimum if the square expected value of the next error signal is less than the square expected value of the error signal, the method comprises: When the square expected value of the error signal reaches a minimum, a weight coefficient is determined and used as a target weight coefficient of the adaptive filter.

3. The method according to claim 1, characterized in that The redriver includes a storage control module, wherein the storage control module establishes a communication connection with the adaptive filter; The obtaining of the desired signal by the adaptive filter comprises: Acquiring an initial signal through the storage control module; When the storage control module acquires the initial signal, the initial signal is used as the expected signal, and the expected signal is sent to the adaptive filter.

4. The method according to claim 1, characterized in that: The predetermined target gradient includes: Taking the square value of any of the error signals as the instantaneous square value of the error signal; Performing an approximate gradient operation on the instantaneous square value of the error signal to obtain an approximate gradient; The approximate gradient is taken as the target gradient.

5. A signal processing system, characterized in that: The signal processing system includes an adaptive filter and a signal preprocessing module; The signal preprocessing module is used to perform preliminary filtering on the attenuated signal to be processed through the input buffer stage to obtain a filtered attenuated signal; when the filtered attenuated signal is obtained, the filtered attenuated signal is sent to the high-speed analog-to-digital converter through the input buffer stage; In the case where the high-speed analog-to-digital converter receives the filtered attenuation signal, performing signal conversion processing on the filtered attenuation signal to obtain a digital attenuation signal, sending the digital attenuation signal to the adaptive filter, performing signal conversion processing on the target output signal through the high-speed digital-to-analog converter to obtain an analog target output signal, and sending the analog target output signal to the output amplifier stage, performing signal amplification processing on the analog target output information through the output amplifier stage to obtain a processed target output signal; The adaptive filter is used to obtain an expected signal, an attenuated signal and a weight coefficient of the adaptive filter, wherein the attenuated signal is formed by attenuation of the expected signal during transmission in a signal transmission path, and when the attenuated signal and the weight coefficient of the adaptive filter are obtained, the attenuated signal and the weight coefficient of the adaptive filter are convolved to obtain an actual output signal, and when the adaptive filter obtains the expected signal and the actual output signal, an error signal is determined according to the expected signal and the actual output signal, the square value of the error signal is determined according to the error signal, and the square value of the error signal is obtained according to the square of the error signal. The method further comprises the steps of determining a square expected value of the error signal according to a square value of the error signal, repeatedly performing the steps of obtaining an error signal through the adaptive filter, determining a square value of the error signal according to the error signal, and determining a square expected value of the error signal according to the square value of the error signal, obtaining a square expected value of a next error signal, and if the square expected value of the next error signal is greater than or equal to the square expected value of the error signal, determining that the square expected value of the error signal reaches a minimum; if the square expected value of the next error signal is less than the square expected value of the error signal, determining that the square expected value of the error signal does not reach a minimum; and if the square expected value of the error signal does not reach a minimum, repeatedly performing the steps of determining a square expected value of the error signal according to the adaptive filter. Determine a target gradient and a convergence factor, determine a new weight coefficient of the adaptive filter according to the current weight coefficient of the adaptive filter, the convergence factor and the target gradient, obtain an error signal through the adaptive filter, determine the square value of the error signal according to the error signal, determine the square expected value of the error signal according to the square value of the error signal, and determine whether the square expected value of the error signal reaches a minimum, until the square expected value of the error signal reaches a minimum, determine the weight coefficient, and use the weight coefficient as the target weight coefficient of the adaptive filter, or repeatedly update the convergence factor of the adaptive filter through the adaptive filter The error signal is obtained, a square value of the error signal is determined according to the error signal, a square expected value of the error signal is determined according to the square value of the error signal, and a step of judging whether the square expected value of the error signal reaches a minimum is performed until the square expected value of the error signal reaches a minimum, a weight coefficient is determined, and the weight coefficient is used as a target weight coefficient of the adaptive filter, the adaptive filter is configured according to the target weight coefficient to obtain a target adaptive filter, and the digital attenuation signal is convolved based on the target weight coefficient through the target adaptive filter to obtain a target output signal, and the target output signal is sent to the high-speed digital-to-analog converter.

6. An electronic device, characterized in that: include: a memory for storing processor-executable instructions; The processor is configured to execute the instructions to implement the steps of the signal processing method according to any one of claims 1 to 4.

7. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the signal processing method according to any one of claims 1 to 4 are implemented.

8. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the signal processing method according to any one of claims 1 to 4 are implemented.

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