A square wave driving timing control method, system, device and medium

Abstract

The application discloses a square wave driving timing control method, relates to the technical field of driving signal processing, and comprises the following steps: S1, acquiring an initial square wave waveform, wherein the initial square wave waveform comprises a rising edge and a falling edge; S2, performing expansion calculation on the rising edge and the falling edge to obtain an expanded waveform model of the entire initial square wave waveform; S3, performing calculation processing on the expanded waveform model based on a filter optimization algorithm to generate optimization parameters; S4, acquiring square wave driving timing according to the optimization parameters; and S5, controlling liquid crystal terminal work according to the square wave driving timing. The application further provides a square wave driving timing control system. The application has the advantages of high-precision waveform description, an optimized filter process and improved display stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of driving signal processing, in particular to a square wave driving timing control method, system, device and medium. BACKGROUND

[0002] As a key means of controlling the switching state of liquid crystal molecules, the accuracy and stability of square wave driving timing directly affect the image quality of display panels. Traditionally, the timing of driving signals, including rising and falling edges, is usually set with a unified specification. This "one-size-fits-all" timing setting method has been widely used in various liquid crystal displays in the past. However, with the rapid development of display industry technology, especially the continuous improvement of panel resolution and refresh rate, the traditional square wave driving timing setting method has gradually exposed many limitations.

[0003] On the one hand, due to the diversity of liquid crystal display technology, different liquid crystal materials and display panels have different timing requirements for driving signals. The traditional unified specification timing setting method cannot be optimized for specific liquid crystal display technology, resulting in low matching degree between driving signals and liquid crystal display panels, which affects the display effect. On the other hand, with the improvement of panel resolution and refresh rate, the rising and falling edges in liquid crystal driving timing become particularly important. The traditional timing setting method often cannot accurately control the shape and speed of the rising and falling edges, resulting in distortion of driving signals and generation of parasitic signals. These distortions and parasitic signals can seriously interfere with the normal switching state of liquid crystal molecules, and further cause abnormal phenomena on the display panel, such as vertical bright and dark lines, which seriously affect the user's viewing experience. SUMMARY

[0004] In view of the defects in the prior art, the present application provides a square wave driving timing control method, system, device and medium.

[0005] A square wave driving timing control method, comprising: S1, obtaining an initial square wave waveform, the initial square wave waveform comprising a rising edge and a falling edge; S2, performing expansion calculation on the rising edge and the falling edge and obtaining an expanded waveform model of the entire initial square wave waveform; S3, performing calculation and processing on the expanded waveform model based on a filtering optimization algorithm and generating optimization parameters; S4, obtaining square wave driving timing according to the optimization parameters; S5, controlling the work of a liquid crystal terminal according to the square wave driving timing.

[0006] Preferably, S3 comprises: S31, setting an initial filter parameter; S32, performing filter calculation on the unfolded waveform model based on a filter optimization algorithm and the initial filter parameter to obtain a filtered square wave model; performing calculation on the filtered square wave model based on the filter optimization algorithm and obtaining a real-time quantization index, the quantization index being used to quantify a real-time distortion value of the filtered square wave model; judging whether the real-time distortion value is greater than a preset threshold; S33, if yes, reducing the initial filter parameter and obtaining a modified filter parameter, and continuing to start S32 after replacing the initial filter parameter with the modified filter parameter, so as to continuously iterate the filter parameter; if no, outputting the latest filter parameter as an optimized parameter.

[0007] Preferably, S32 comprises: S321, setting a sampling frequency, sampling the unfolded waveform model at the sampling frequency and obtaining a discrete-time model; S322, calculating a filter index based on the filter optimization algorithm, the initial filter parameter and the sampling frequency; S323, processing the discrete-time model based on the filter optimization algorithm and the filter index and obtaining the filtered square wave model; S324, performing calculation on the filtered square wave model based on the filter optimization algorithm and obtaining a real-time quantization index; S325, judging whether the real-time quantization index is greater than a preset threshold.

[0008] Preferably, S324 comprises: S3241, performing frequency spectrum analysis on the filtered square wave model and obtaining frequency spectrum components; S3242, calculating the real-time quantization index based on the filter optimization algorithm and the frequency spectrum components.

[0009] Preferably, the calculation process of the filter optimization algorithm in S322 can be represented as: wherein, a is the filter index, W1 is the initial filter parameter, f c is the sampling frequency.

[0010] Preferably, the filter optimization algorithm in S323 can be represented as: y[n]=(1-α)·g[n]+α·

[0011] y[n-1], N≥n≥1; wherein, N is the length of the discrete-time model based on the sampling frequency, g[n] is a square wave signal of the nth sampling point in the discrete-time model, y[n-1] is a square wave signal of the (n-1)th sampling point in the filtered square wave model, and y[n] is a square wave signal of the nth sampling point in the filtered square wave model.

[0012] Preferably, the calculation process of the filter optimization algorithm in S3242 can be represented as: ×100%; wherein, D is the real-time quantization index, V n is the nth frequency spectrum component of the filtered square wave model.

[0013] The application further provides a square wave driving timing control system for implementing the square wave driving timing control method, the system comprising: an acquisition module for acquiring an initial square wave waveform, the initial square wave waveform comprising a rising edge and a falling edge; a first calculation module for performing expansion calculation on the rising edge and the falling edge and obtaining an expanded waveform model of the entire initial square wave waveform; a second calculation module for performing calculation processing on the expanded waveform model based on a filter optimization algorithm and generating optimization parameters; a waveform correction module for acquiring square wave driving timing according to the optimization parameters; and a control module for controlling the working of a liquid crystal terminal according to the square wave driving timing.

[0014] The application further provides an electronic device comprising: a memory having a computer program stored thereon; and a processor for executing the computer program in the memory to implement the square wave driving timing control method.

[0015] The application further provides a non-transitory computer readable storage medium having a computer program stored thereon, the program being executed by a processor to implement the square wave driving timing control method.

[0016] The application has the following beneficial effects:

[0017] In the square wave driving timing control method, the initial square wave waveform data is acquired, and the rising edge and the falling edge are subjected to detailed expansion calculation, so that the detailed features of the square wave waveform can be more accurately described, which makes the matching degree between the driving signal and the liquid crystal display panel higher, so as to accurately control the on-off state of the liquid crystal molecules and reduce image distortion, flicker and other problems; further, the expanded waveform model is processed and analyzed by using the filter optimization algorithm, which can eliminate noise, jitter and other adverse factors in the waveform, which is helpful to generate more stable and reliable driving signals and further improve the stability of the display effect; further, the traditional square wave driving timing setting method adopts a unified specification and cannot be optimized for specific liquid crystal display technologies, while the technical solution can adapt to the timing requirements of different liquid crystal materials and display panels through in-depth analysis and optimization of the square wave waveform, so as to improve the display effect; further, stable square wave driving timing can help to reduce the accumulation of mechanical stress and thermal stress of the liquid crystal display panel during working, thereby prolonging its service life, which helps to reduce the maintenance cost and replacement frequency of users and improve the satisfaction of users, and similar driving timing optimization methods can be explored in the fields of LED display, OLED display and the like to improve the display effect and stability. BRIEF DESCRIPTION OF DRAWINGS

[0018] In order to more clearly illustrate the technical solutions in the specific embodiments of the present application or the prior art, the following will briefly introduce the drawings needed in the specific embodiments or prior art description. In all the drawings, similar elements or parts are generally identified by similar reference signs. In the drawings, the elements or parts are not necessarily drawn according to the actual proportions.

[0019] Figure 1 A schematic diagram of the steps of the square wave driving timing control method of the present application;

[0020] Figure 2 A schematic diagram of the steps of S3 in the square wave driving timing control method of the present application;

[0021] Figure 3 A schematic diagram of the steps of S32 in the square wave driving timing control method of the present application;

[0022] Figure 4 A schematic diagram of the steps of S324 in the square wave driving timing control method of the present application;

[0023] Figure 5 A block diagram of an electronic device according to an embodiment of the present application.

[0024] Reference signs:

[0025] 700 - electronic device, 701 - processor, 702 - memory, 703 - multimedia component, 704 - input / output (I / O) interface, 705 - communication component. DETAILED DESCRIPTION

[0026] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will combine the drawings in the embodiments of the present application to make a clear and complete description of the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0027] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative labor are within the scope of protection of the present application.

[0028] It should be noted that: similar reference signs and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.

[0029] As shown in Figure 1 , a square wave driving timing control method is provided, comprising:

[0030] S1, obtaining an initial square wave waveform, the initial square wave waveform comprising a rising edge and a falling edge;

[0031] S2, performing unfolding calculation on the rising edge and the falling edge and obtaining an unfolded waveform model of the entire initial square wave waveform;

[0032] S3, performing calculation and processing on the unfolded waveform model based on a filtering optimization algorithm and generating optimization parameters;

[0033] S4, obtaining square wave driving timing according to the optimization parameters;

[0034] S5, controlling the liquid crystal terminal to work according to the square wave driving timing.

[0035] In this embodiment, it should be noted that in S1, initial square wave waveform data is obtained. This initial square wave waveform is the basis for all subsequent processing and analysis, so its accuracy and integrity are crucial. When obtaining the initial square wave waveform, special attention should be paid to the rising edge and the falling edge. The rising edge represents the process of the signal transitioning from low to high, while the falling edge represents the process of the signal transitioning from high to low. These two processes have a direct impact on the switching state of the liquid crystal molecules, so they are the most critical parts of the square wave waveform. For example: assuming that a certain liquid crystal display panel requires a rising edge time of 100 ns and a falling edge time of 80 ns for the driving signal, through S1 step, we can use a high-speed oscilloscope to capture the initial square wave waveform of the panel in actual work, which includes the timing and shape of the rising edge and the falling edge. In this way, in the subsequent S2 step, we can perform unfolding calculation on the rising edge and the falling edge based on these accurate data to obtain a more accurate waveform model.

[0036] In S2, based on in-depth analysis of the initial square wave waveform, especially detailed unfolding calculation of the rising edge and the falling edge, the purpose is to smooth the rising edge and the falling edge so as to describe them with more continuous mathematical functions. Since the rising edge and the falling edge are usually steep, i.e. the time required for high-low level change is very short, we can consider using Taylor expansion or other unfolding methods to approximate these steep changes. Here, the unfolded rising edge and falling edge use the smoothing characteristics of trigonometric functions (especially sine and cosine functions) to simulate the rising edge and the falling edge, which can capture and filter out the nonlinear changes of other non-trigonometric functions in these two parts of the timing. For example: assuming that the time when the rising edge starts is t r-start , and the time when the rising edge ends is t r-end , the trigonometric function model of the rising edge can be expressed as: Let the time when the falling edge starts be t f-start , and the time when it ends be The trigonometric model of the rising edge can be expressed as: The expanded waveform model of the entire square wave waveform can be expressed as: where it is assumed that the time period from 0 to t f-end is exactly the period T of the square wave. In summary, through expansion calculation, the detailed characteristics of the square wave waveform can be more accurately described, especially the rising edge and falling edge parts, which can accurately capture and filter out other inappropriate nonlinear changes in the timing of these two parts, thereby improving the accuracy and reliability of the waveform model. Further, the accurate waveform model provides a solid foundation for subsequent filtering optimization algorithms, enabling the optimization process to more effectively address specific issues in the waveform and generate higher-quality drive signals.

[0037] In S3, the expanded waveform model obtained in S2 is further processed and analyzed using a filtering optimization algorithm to eliminate noise, jitter, and other adverse factors in the waveform, while optimizing the shape and speed of the rising edge and falling edge, providing a basis for generating more accurate and stable drive signals. Through the processing of the filtering optimization algorithm, optimization parameters can be obtained, which are generally the filter cutoff frequency, which can describe the key fundamental frequency characteristics of the optimized square wave waveform.

[0038] In S4, for example, the optimization parameter is the filter cutoff frequency, which directly serves as the fundamental frequency of the optimized square wave waveform, so the period of the optimized square wave waveform is the inverse of the fundamental frequency, thereby directly obtaining the entire square wave drive timing. We can use Python code here to automatically generate the square wave timing:

[0039] 1import numpy as np

[0040] 2import matplotlib.pyplot as plt

[0041] 3# Set the cutoff frequency (fundamental frequency)

[0042] 4 f_c = 1000 # Hz, for example 1000 Hz

[0043] 5 # Calculate the period

[0044] 6 T = 1 / f_c

[0045] 7 # Set the high level and low level of the square wave

[0046] 8 high_level = 1

[0047] 9 low_level = 0

[0048] 10 # Set the length of time to generate square wave

[0049] 11 duration = 0.01 # seconds, for example, generate a 0.01 second time sequence

[0050] 12 # Generate time sequence

[0051] 13 t = np.arange(0, duration, T / 100) # Subdivide each cycle into 100 points

[0052] 14 # Generate square wave

[0053] 15 square_wave = np.where(np.mod(t, T) < T / 2, high_level, low_level)

[0054] 16 # Draw square wave

[0055] 17 plt.plot(t, square_wave)

[0056] 18 plt.title('Square Wave')

[0057] 19 plt.xlabel('Time[s]')

[0058] 20 plt.ylabel('Amplitude')

[0059] 21 plt.grid(True)

[0060] 22 plt.show()

[0061] where f_c is the cutoff frequency, T is the calculation period, high_level and low_level are the high and low levels, duration is the length of time to generate the square wave, t is the generated time sequence, square_wave is the square wave generated using the np.where function (in each cycle, the first half is set to high level, and the second half is set to low level), and plt.plot is the square wave drawn using the Matplotlib library.

[0062] In S5, the optimized square wave driving timing is applied to the control system of the liquid crystal terminal to realize accurate control of the switching state of the liquid crystal molecules. Among them, the square wave driving timing is transmitted to the liquid crystal display driving chip through a suitable interface (such as SPI, I2C, etc.), and the driving chip generates the corresponding driving signal according to the square wave driving timing data, and then drives the liquid crystal molecules on the liquid crystal panel to switch according to the predetermined timing.

[0063] In summary, in the whole square wave driving timing control method, by obtaining the initial square wave waveform data and performing detailed expansion calculation on the rising edge and the falling edge, the details of the square wave waveform can be more accurately described, which makes the matching degree between the driving signal and the liquid crystal display panel higher, so as to accurately control the switching state of the liquid crystal molecules and reduce the problems such as image distortion and flicker; further, the expansion waveform model is processed and analyzed by using the filtering optimization algorithm, which can eliminate the noise, jitter and other adverse factors in the waveform, which is helpful to generate more stable and reliable driving signal and further improve the stability of the display effect; further, the traditional square wave driving timing setting method adopts a unified specification and cannot be optimized for specific liquid crystal display technology, while the technical solution can adapt to the timing requirements of different liquid crystal materials and display panels through in-depth analysis and optimization of the square wave waveform, thereby improving the display effect; further, stable square wave driving timing can help reduce the accumulation of mechanical stress and thermal stress of the liquid crystal display panel during work, thereby prolonging its service life, which helps to reduce the maintenance cost and replacement frequency of the user and improve the user's satisfaction. In the field of LED display, OLED display and the like, similar driving timing optimization methods can also be explored to improve the display effect and stability.

[0064] As shown in FIG. 1, Figure 2 In one embodiment, S3 includes:

[0065] S31, setting initial filtering parameters;

[0066] S32, filtering calculation is performed on the expansion waveform model based on the filtering optimization algorithm and the initial filtering parameters to obtain a filtered square wave model; the filtering optimization algorithm is used to calculate the filtered square wave model and obtain a real-time quantization index, which is used to quantify the real-time distortion value of the filtered square wave model; it is judged whether the real-time distortion value is greater than a preset threshold value;

[0067] S33, if yes, the initial filtering parameters are reduced to obtain modified filtering parameters, and the modified filtering parameters are replaced by the initial filtering parameters to continue S32, and the filtering parameters are iterated in this way; if not, the latest filtering parameters are output as the optimized parameters.

[0068] In this embodiment, it is noted that in S31, a starting point is provided for the filter optimization algorithm to start the iteration process. The initial filter parameters, such as the cutoff frequency, bandwidth, or order of the filter, can be set based on experience or experimental data.

[0069] In S32, the unfolded waveform model is filtered using a filter optimization algorithm (such as FIR filter, IIR filter, Kalman filter, etc.) and initial filter parameters to obtain a filtered square wave model. Then, a real-time quantification index is calculated, which quantifies the real-time distortion value of the filtered square wave model. The distortion value may include waveform distortion, phase distortion, amplitude distortion, etc. Finally, a judgment is made to compare the real-time distortion value with the preset threshold value. If the real-time distortion value is greater than the preset threshold value, it indicates that the filtering effect is not ideal and the filter parameters need to be adjusted. If the real-time distortion value is less than or equal to the preset threshold value, it indicates that the filtering effect meets the requirements. At the same time, the setting of the preset threshold value is a key step in liquid crystal display technology, which is usually determined according to the specific parameters of the liquid crystal terminal. These parameters may include the characteristics of the liquid crystal material, the resolution, refresh rate, response time of the display panel, and the performance of the driving circuit, etc. When setting the preset threshold value, the overall performance and display effect requirements of the liquid crystal terminal need to be considered comprehensively. For example, if the liquid crystal material is sensitive to changes in filter parameters, or the resolution and refresh rate of the display panel are high, the preset threshold value may need to be set more strictly to ensure that the waveform distortion value after filtering is within an acceptable range.

[0070] In S33, if the real-time distortion value is greater than the preset threshold value (the result of the judgment in S32), the initial filter parameters are reduced (such as reducing the cutoff frequency, increasing the filter order, etc.) to obtain modified filter parameters. After replacing the initial filter parameters with the modified filter parameters, return to S32 to continue the new round of filter calculation and distortion value judgment. Iteration termination: if the real-time distortion value is less than or equal to the preset threshold value (the result of the judgment in S32), output the latest filter parameters as the optimized parameters (i.e. the filter cutoff frequency required in S4).

[0071] Through this subdivided S3 step, the filter process can be more accurately controlled and optimized to ensure that the filtered square wave model has a lower distortion value and better stability. This iterative optimization method helps to adapt to different liquid crystal materials and timing requirements of display panels, thereby improving the display effect and user viewing experience. At the same time, by setting a reasonable preset threshold value and iteration strategy, the calculation amount and iteration times can be reduced while ensuring the filtering effect, improving the efficiency of the algorithm.

[0072] As shown in FIG. 4, in one embodiment, S32 includes: Figure 3

[0073] ​S321. Set the sampling frequency, sample the expanded waveform model according to the sampling frequency, and obtain the discrete-time model;

[0074] S322. Calculate the filter index based on the filter optimization algorithm, initial filter parameters, and sampling frequency; the calculation process of the filter optimization algorithm in S322 can be expressed as follows: Where α is the filter exponent, W1 is the initial filter parameter, and f c The sampling frequency;

[0075] S323. Based on the filtering optimization algorithm and the filtering exponent, the discrete-time model is processed to obtain the filtered square wave model; the filtering optimization algorithm in S323 can be expressed as: y[n]=(1-α)·g[n]+α·y[n-1], N≥n≥1; where N is the length of the discrete-time model based on the sampling frequency, g[n] is the square wave signal of the nth sampling point in the discrete-time model, y[n-1] is the square wave signal of the (n-1)th sampling point in the filtered square wave model, and y[n] is the square wave signal of the nth sampling point in the filtered square wave model;

[0076] S324. Calculate the filtered square wave model based on the filtering optimization algorithm and obtain the real-time quantization index;

[0077] S325. Determine whether the real-time quantitative indicator is greater than the preset threshold.

[0078] In this embodiment, it should be noted that in S321, a sampling frequency f is set. c Then with f c By sampling g(t), a new discrete-time model g[t] is obtained.

[0079] In S322, firstly, the filtering optimization algorithm is used... This calculation process expression, substituting the initial filter parameters S31 to obtain W1 and S321 to obtain f c The filter exponent α is calculated. Here, the initial filter parameter W1 is the initial cutoff frequency. This expression can effectively attenuate signals above the initial cutoff frequency; at the same time, the expression ensures the stability of the filter, since the value of α is between 0 and 1 (when W1 and f...). c When all numbers are positive, this ensures that the subsequent calculation process of the filtered square wave model will not diverge; therefore, the entire expression is crucial for implementing low-pass filtering, simplifying calculations, ensuring stability, providing adjustability, and has a clear physical meaning.

[0080] In S323, the calculation process expression y[n]=(1-α)·g[n]+α·y[n-1] in the filtering optimization algorithm is used, and α obtained in S322 is substituted into it. y[0] is used as the initial value, which can be set to y[0]=0. Then, y[1], y[2], ..., y[n] are calculated sequentially. The square wave signals of these sampling points form the entire discrete filtered square wave model y[t]. Filtering is achieved through this expression. The attenuation of high-frequency components is controlled by α. At the same time, the current input signal g[n] and the previous filtered output y[n-1] are combined to achieve a smooth filtering effect, realize effective filtering optimization, and ensure that the filtered signal meets the distortion and performance requirements.

[0081] In S324, the distortion value of the filtered square wave model is quantized for subsequent judgment and optimization. Distortion is calculated using a filtering optimization algorithm to obtain real-time quantization indicators. These indicators may include waveform distortion, phase error, amplitude deviation, etc., and are used to quantify the difference between the filtered square wave model and the ideal square wave.

[0082] In S325, it is determined whether the distortion value of the filtered square wave model exceeds the acceptable range. If the real-time quantization index is greater than the preset threshold, it indicates that the filtering effect is not ideal; if the real-time quantization index is less than or equal to the preset threshold, it indicates that the filtering effect meets the requirements.

[0083] like Figure 4 As shown, in one embodiment, S324 includes:

[0084] S3241. Perform spectral analysis on the filtered square wave model and obtain the spectral components;

[0085] S3242. Real-time quantization metrics are obtained based on the filter optimization algorithm and spectral component calculation; the calculation process of the filter optimization algorithm in S3242 can be expressed as follows: Where D is a real-time quantitative indicator, and V n This represents the nth spectral component of the filtered square wave model.

[0086] In this embodiment, it should be noted that in S3241, spectral analysis is performed on the filtered square wave model y[t] to obtain its spectral components V. nGenerally, it can be completed by existing technical means such as discrete Fourier transform (DFT) or fast Fourier transform (FFT). For example: based on the filtered square wave model y[t], that is, the filtered discrete-time signal y[n], it is judged whether the length N is a power of 2. If not, zero is added at the end to meet this condition, so that it is convenient to use DFT; when DFT is performed on y[n], existing programming languages and numerical calculation tools (such as Python's NumPy library, MATLAB, etc.) have ready-made DFT functions; the result obtained by DFT is the frequency spectrum component of the discrete-time signal, which represents the amplitude and phase of the spectrum.

[0087] In S3242, the filter optimization algorithm is used to calculate the filter parameters based on the spread waveform model This calculation process expression, V1 is the fundamental component, by substituting y[n] of the above obtained discrete Fourier transform of the nth spectrum component V n .

[0088] It should be noted that according to the result of judging whether D is greater than the preset threshold, it may be necessary to adjust the cutoff frequency f c of the filter. For example, if D is high and there are many high-frequency components, the cutoff frequency f c is directly reduced. Then apply the calculation of D again, and iteratively perform this process until D reaches an acceptable level, or the waveform quality cannot be further improved by adjusting the cutoff frequency.

[0089] Through iterative calculation, the cutoff frequency can be gradually adjusted until the optimal filter parameters are found. In this process, we will find that the high-frequency component gradually decreases, D gradually decreases, and the waveform distortion and burr are effectively controlled.

[0090] A square wave driving timing control system is also provided, which is used to implement the square wave driving timing control method in any of the above embodiments. The system comprises:

[0091] An acquisition module is configured to acquire a preliminary square wave waveform, which includes a rising edge and a falling edge.

[0092] A first calculation module is configured to perform spread calculation on the rising edge and the falling edge and obtain a spread waveform model of the entire preliminary square wave waveform.

[0093] A second calculation module is configured to perform calculation and processing on the spread waveform model based on a filter optimization algorithm and generate optimization parameters.

[0094] A waveform correction module is configured to acquire a square wave driving timing according to the optimization parameters.

[0095] A control module is configured to control the work of a liquid crystal terminal according to the square wave driving timing.

[0096] In the present embodiment, it is to be noted that, as to the above-mentioned square wave driving timing control system, the specific manner in which operations are performed has been described in detail in the embodiments related to the square wave driving timing control method, and will not be described in detail here.

[0097] Figure 5 is a block diagram of an electronic device according to an example embodiment. As shown, the electronic device 700 can include a processor 701, a memory 702. The electronic device 700 can also include one or more of a multimedia component 703, an input / output (I / O) interface 704, and a communication component 705. Figure 5

[0098] ​The processor 701 is configured to control overall operations of the electronic device 700 to complete all or part of the steps of the square wave driving timing control method described above. The memory 702 is configured to store various types of data to support operations of the electronic device 700, which can include, for example, instructions for any application or method operating on the electronic device 700, and application-related data, such as contact data, transmitted and received messages, pictures, audio, video, and the like. The memory 702 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic storage, a flash memory, a magnetic disk, or an optical disk. The multimedia component 703 can include a screen and an audio component. The screen can be, for example, a touch screen, and the audio component is configured to output and / or input audio signals. For example, the audio component can include a microphone configured to receive external audio signals. The received audio signals can be further stored in the memory 702 or transmitted through the communication component 705. The audio component further includes at least one speaker configured to output audio signals. The I / O interface 704 provides an interface between the processor 701 and other interface modules, which can be a keyboard, a mouse, a button, and the like. The buttons can be virtual buttons or physical buttons. The communication component 705 is configured to perform wired or wireless communication between the electronic device 700 and other devices. The wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G, 4G, NB-IOT, eMTC, or other 5G, and the like, or a combination of one or more of them, is not limited herein. Therefore, the communication component 705 can include, for example, a Wi-Fi module, a Bluetooth module, an NFC module, and the like.

[0099] In an exemplary embodiment, the electronic device 700 can be implemented by one or more Application Specific Integrated Circuits (ASICs), Digital Signal Processors (DSPs), Digital Signal Processing Devices (DSPDs), Programmable Logic Devices (PLDs), Field Programmable Gate Arrays (FPGAs), controllers, micro-controllers, microprocessors, or other electronic elements for performing the square wave driving timing control method described above.

[0100] In another exemplary embodiment, a computer readable storage medium including program instructions is also provided, which, when executed by a processor, implement the steps of the square wave driving timing control method described above. For example, the computer readable storage medium can be the memory 702 described above including program instructions, which can be executed by the processor 701 of the electronic device 700 to complete the square wave driving timing control method described above.

[0101] In another exemplary embodiment, a computer program product is also provided, which contains a computer program executable by a programmable apparatus, the computer program having code portions for performing the square wave driving timing control method described above when executed by the programmable apparatus.

[0102] The preferred embodiments of the present disclosure are described in detail above with reference to the accompanying drawings, but the present disclosure is not limited to the specific details of the above-described embodiments. Within the technical concept scope of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.

[0103] In addition, it should be noted that each specific technical feature described in the above specific embodiments can be combined in any appropriate manner without contradiction. In order to avoid unnecessary repetition, various possible combinations are not described again by the present disclosure.

[0104] In addition, any combination of various different embodiments of the present disclosure can also be made, as long as it does not deviate from the idea of the present disclosure, it should also be considered as disclosed by the present disclosure.

[0105] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the present application; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some or all of the technical features can be replaced by equivalent replacements; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should be covered in the scope of the claims and the description of the present application.

Claims

1. A square wave drive timing control method, characterized by, The method comprises the following steps: S1, acquiring an initial square wave form, the initial square wave form comprising a rising edge and a falling edge; S2, performing unfolding calculation on the rising edge and the falling edge to obtain an unfolded wave form model of the initial square wave form; S3, performing calculation and processing on the unfolded wave form model based on a filter optimization algorithm to generate an optimization parameter; S3 comprises: S31, setting an initial filter parameter; S32, performing filter calculation on the unfolded wave form model based on the filter optimization algorithm and the initial filter parameter to obtain a filtered square wave model; performing calculation on the filtered square wave model based on the filter optimization algorithm to obtain a real-time quantization index, the quantization index being used to quantify a real-time distortion value of the filtered square wave model; judging whether the real-time distortion value is greater than a preset threshold; S33, if yes, reducing the initial filter parameter to obtain a corrected filter parameter, and continuing to start S32 after replacing the initial filter parameter with the corrected filter parameter to iteratively correct the filter parameter; if no, outputting the latest filter parameter as the optimization parameter; S32 comprises: S321, setting a sampling frequency, sampling the unfolded wave form model at the sampling frequency to obtain a discrete time model; S322, calculating a filter index based on the filter optimization algorithm, the initial filter parameter and the sampling frequency; S323, processing the discrete time model based on the filter optimization algorithm and the filter index to obtain the filtered square wave model; S324, performing calculation on the filtered square wave model based on the filter optimization algorithm to obtain the real-time quantization index; S325, judging whether the real-time quantization index is greater than the preset threshold; S4, acquiring a square wave driving timing sequence according to the optimization parameter; S5, controlling a liquid crystal terminal to work according to the square wave driving timing sequence.

2. The square wave drive timing control method according to claim 1, wherein S324 comprises: S3241, performing frequency spectrum analysis on the filtered square wave model to obtain a frequency spectrum component; S3242, calculating the real-time quantization index based on the filter optimization algorithm and the frequency spectrum component.

3. The square wave drive timing control method according to claim 1, wherein The calculation process of the filter optimization algorithm in S322 can be represented as: ; wherein, is a filter index, is an initial filter parameter, is a sampling frequency.

4. The square wave drive timing control method according to claim 1, wherein The filter optimization algorithm in S323 can be represented as: , ; wherein, is the length of the discrete-time model based on the sampling frequency, is the square wave signal at the n-th sample point in the discrete-time model, is the square wave signal at the n-1-th sample point in the filtered square wave model, is the square wave signal at the n-th sample point in the filtered square wave model.

5. The square wave drive timing control method according to claim 1, wherein The calculation process of the filter optimization algorithm in S3242 can be represented as: ; wherein, for real-time quantification metrics, is the nth spectral component of the filtered square wave model.

6. A square wave drive timing control system characterized by, The system is used to implement the square wave driving timing control method in any one of claims 1 to 5, and the system comprises: an acquisition module, configured to acquire an initial square wave form, the initial square wave form comprising a rising edge and a falling edge; a first calculation module, configured to perform unfolding calculation on the rising edge and the falling edge to obtain an unfolded wave form model of the initial square wave form; a second calculation module, configured to perform calculation and processing on the unfolded wave form model based on a filter optimization algorithm to generate an optimization parameter; a wave form correction module, configured to acquire a square wave driving timing sequence according to the optimization parameter; a control module, configured to control a liquid crystal terminal to work according to the square wave driving timing sequence.

7. An electronic device, comprising: The method comprises the following steps: a memory having a computer program stored thereon; a processor configured to execute the computer program in the memory to implement the square wave driving timing control method in any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to implement the square wave driving timing control method in any one of claims 1 to 5.

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