Event-driven communication and device for multi-threshold quantization system

Abstract

This invention provides an event-driven communication method and apparatus for a multi-threshold quantization system, relating to the field of communication technology. The method includes: acquiring the input vector of an FIR system; obtaining the output vector through the FIR system based on the input vector, and then obtaining a measurement vector through a multi-threshold quantizer with m thresholds; dynamically adjusting the trigger reference value of an event trigger based on the data frequency of the completed transmission using the measurement vector independently counted by both the sender and receiver; obtaining a trigger state value by comparing the measurement vector with the reference value; and generating a transmission value by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center, which estimates the unknown parameters of the FIR system based on the transmission value. This invention reduces the number of communication operations while ensuring data integrity without increasing additional computation or feedback communication.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to an event-driven communication method and apparatus for a multi-threshold quantization system. Background Technology

[0002] With the rapid development of computer and network communication technologies, traditional control systems, limited by localized control and decision-making, are gradually failing to meet the demands of complex real-world applications. Networked Control Systems (NCSs), through shared network connection nodes, utilize network technology to achieve remote distributed control and decision-making, significantly improving system efficiency and flexibility, and thus have become an important research direction. Currently, NCSs are widely used in transportation systems, power systems, and microgrids. Finite Impulse Response (FIR) systems are a common type of networked control system. However, the continuous increase in subsystems and the surge in corresponding devices and sensors have led to an exponential increase in data transmission volume. How to optimize transmission to save channel resources, reduce bandwidth consumption, and effectively transmit data to the estimation center has become an urgent problem to be solved.

[0003] Given this need, quantizing transmitted data is one direction. Simultaneously, due to limitations in sensor accuracy and cost, their outputs are also quantized. However, the information loss resulting from quantization increases the difficulty of identification. Therefore, research on system identification based on quantized observations has received widespread attention. Furthermore, event-driven mechanisms are also an effective method for conserving communication resources, attracting considerable scholarly attention and yielding many excellent results.

[0004] The identification of FIR systems is influenced by both multi-threshold quantization and event-driven mechanisms. Quantization loses information from the data, and the event-driven mechanism disrupts the integrity of measurement information. The coupling between these two factors results in high nonlinearity of the system, significantly increasing the difficulty of system parameter identification. Summary of the Invention

[0005] To address the technical challenge of high parameter identification difficulty in existing FIR systems, this invention provides an event-driven communication method and apparatus for a multi-threshold quantization system. The technical solution is as follows:

[0006] On the one hand, an event-driven communication method for a multi-threshold quantization system is provided, including:

[0007] Obtain the input vector of the FIR system;

[0008] Based on the input vector, after obtaining the output vector through the FIR system, the measurement vector is obtained by measuring through a multi-threshold quantizer with m thresholds;

[0009] The frequency of data transmission is determined by independently statistically analyzed measurement vectors from both the sender and receiver. The trigger reference value is dynamically adjusted, and a trigger state value is obtained by comparing the measurement vector with the reference value. The transmission value is generated by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center via a communication network. The remote estimation center then estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is:

[0010] Thirdly, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

[0011] Optionally, the remote estimation center processes the received data using Formula 2, which is:

[0012]

[0013]

[0014]

[0015] in, Used to estimate the unknown parameters of the FIR system, initial values N τ,0 =0,

[0016] Optionally, the FIR system is a single-input single-output finite impulse response system:

[0017]

[0018] Where θ=[a1,…,a n ] T The unknown parameter to be estimated in the system; d k It is system noise with known distribution characteristics; u k The external excitation signal is the system input after being processed by the quantizer. Let r be the number of possible outputs of the quantizer, and let the possible output values ​​of the quantizer be μ1, μ2, ..., μ r , then u k ∈{μ1,μ2,…,μ r};π k =[u k ,…,u k-n+1 ] T It is a vector composed of system inputs.

[0019] Optionally, the value y in the output vector of the FIR system k The value s in the measurement vector is obtained through a multi-threshold quantizer with m thresholds. k Arrange the m threshold values ​​of the sensor from smallest to largest, and denote them as C. w w = 1, 2, ..., m, and -∞ <C1<C2<…<C m If the value is less than ∞, the measurement process can be represented by a function as follows:

[0020]

[0021] Optionally, the value of the event trigger includes 1 and 0. When the value of the event trigger is 1, the value of the measurement vector is sent; when the value of the event trigger is 0, the value of the measurement vector is not sent.

[0022] Optionally, the estimation of unknown parameters of the FIR system by the remote estimation center based on the transmitted value includes:

[0023] The unknown parameters of the FIR system are estimated using Formula 3, which includes:

[0024]

[0025]

[0026] Where {υ r Let {r = 1, ..., m} be m weights, and satisfy the following conditions: F i (x)=F(C i -x).

[0027] Optionally, the parameter estimate It converges strongly to θ.

[0028] On the other hand, an event-driven communication device for a multi-threshold quantization system is also provided. This device is used to implement the event-driven communication method for the multi-threshold quantization system provided in the embodiments of the present invention. The device includes:

[0029] The acquisition module is used to acquire the input vector of the FIR system;

[0030] The measurement module is used to obtain a measurement vector by measuring a multi-threshold quantizer with m thresholds after obtaining an output vector through the FIR system based on the input vector.

[0031] The estimation module dynamically adjusts the trigger reference value of the event trigger based on the data transmission frequency of the measurement vector independently statistically analyzed by both the sender and receiver. It obtains the trigger state value by comparing the measurement vector with the reference value, and generates the transmission value by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center via a communication network, where the remote estimation center estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is:

[0032] in, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

[0033] On the other hand, an event-driven communication device for a multi-threshold quantization system is also provided, the event-driven communication device for the multi-threshold quantization system comprising:

[0034] processor;

[0035] A memory storing computer-readable instructions, which, when executed by the processor, implement the method provided in the embodiments of the present invention.

[0036] On the other hand, a computer-readable storage medium is also provided, wherein program code is stored in the computer-readable storage medium, and the program code can be called by a processor to execute the method provided in the embodiments of the present invention. The beneficial effects brought about by the technical solution provided in the embodiments of the present invention include at least the following:

[0037] This invention, through statistical analysis of the frequency of data occurrence at the sending and receiving ends, dynamically selects non-critical data to suppress transmission, thereby reducing the number of communications while ensuring data integrity without increasing additional computation or feedback communication. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0039] Figure 1 This is a flowchart of an event-driven communication method for a multi-threshold quantization system provided in an embodiment of the present invention;

[0040] Figure 2 This is a system framework diagram of an event-driven communication method for a multi-threshold quantization system provided in an embodiment of the present invention;

[0041] Figure 3 This is a communication rate simulation diagram of an event-driven communication method for a multi-threshold quantization system provided in an embodiment of the present invention;

[0042] Figure 4 This is a simulation diagram illustrating the algorithm convergence of an event-driven communication method for a multi-threshold quantization system provided in an embodiment of the present invention.

[0043] Figure 5 This is a simulation diagram of the asymptotic normality of parameter identification results of an event-driven communication method for a multi-threshold quantization system provided in an embodiment of the present invention;

[0044] Figure 6 This is a schematic diagram of the structure of an event-driven communication device for a multi-threshold quantization system provided in an embodiment of the present invention;

[0045] Figure 7 This is a schematic diagram of the structure of an event-driven communication device for a multi-threshold quantization system provided in an embodiment of the present invention. Detailed Implementation

[0046] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0047] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0048] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, their intended meanings are consistent.

[0049] In this embodiment of the invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0050] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0051] To address the technical challenge of high parameter identification difficulty in existing FIR systems, this invention provides an event-driven communication method and apparatus for a multi-threshold quantization system. The technical solution is as follows:

[0052] On the one hand, such as Figure 1 As shown, an event-driven communication method for a multi-threshold quantization system is provided, including:

[0053] S1. Obtain the input vector of the FIR system;

[0054] S2. Based on the input vector, after obtaining the output vector through the FIR system, the measurement vector is obtained by measuring through a multi-threshold quantizer with m thresholds.

[0055] S3. Based on the data transmission frequency of the measurement vector independently counted by both the sender and receiver, the trigger reference value of the event trigger is dynamically adjusted. The trigger state value is obtained by comparing the measurement vector with the reference value. The transmission value is generated by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center through the communication network. The remote estimation center estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is:

[0056] in, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

[0057] Optionally, the remote estimation center processes the received data using Formula 2, which is:

[0058]

[0059]

[0060]

[0061] in, Used to estimate the unknown parameters of the FIR system, initial values N τ,0 =0,

[0062] Optionally, the FIR system is a single-input single-output finite impulse response system:

[0063]

[0064] Where θ=[a1,…,a n ] T The unknown parameter to be estimated in the system; d k It is system noise with known distribution characteristics; u k The external excitation signal is the system input after being processed by the quantizer. Let r be the number of possible outputs of the quantizer, and let the possible output values ​​of the quantizer be μ1, μ2, ..., μ r , then u k ∈{μ1,μ2,…,μ r};π k =[u k ,…,u k-n+1 ] T It is a vector composed of system inputs.

[0065] Optionally, the value y in the output vector of the FIR system k The value s in the measurement vector is obtained through a multi-threshold quantizer with m thresholds. k Arrange the m threshold values ​​of the sensor from smallest to largest, and denote them as C. w w = 1, 2, ..., m, and -∞ <C1<C2<…<C m If the value is less than ∞, the measurement process can be represented by a function as follows:

[0066]

[0067] Optionally, the value of the event trigger includes 1 and 0. When the value of the event trigger is 1, the value of the measurement vector is sent; when the value of the event trigger is 0, the value of the measurement vector is not sent.

[0068] Optionally, the estimation of unknown parameters of the FIR system by the remote estimation center based on the transmitted value includes:

[0069] The unknown parameters of the FIR system are estimated using Formula 3, which includes:

[0070]

[0071]

[0072] Where {υ r Let {r = 1, ..., m} be m weights, and satisfy the following conditions: F i (x)=F(C i -x).

[0073] Optionally, the parameter estimate It converges strongly to θ.

[0074] This application considers the identification of FIR systems under the combined influence of multi-threshold quantization and event-driven mechanisms. Quantization loses information, and event-driven mechanisms disrupt the integrity of measurement information; their coupling also results in high system nonlinearity, significantly increasing the difficulty of system parameter identification. To overcome this difficulty, this paper proposes an event-driven communication mechanism, FCMQO-EC (Frequency Characteristic of Multi-Threshold Quantized Observations-Event Triggered), based on the frequency characteristics of multi-threshold quantized measurement output, for the case of multi-threshold quantized observations. This mechanism achieves fewer communication cycles while preserving information integrity as much as possible. Simultaneously, under quantized input conditions, an algorithm for identifying unknown parameters of FIR systems based on empirical measures is proposed according to the statistical characteristics of system noise, and the convergence performance of the algorithm is verified.

[0075] This application provides a single-input single-output finite impulse response system:

[0076]

[0077] Where θ=[a1,…,a n ] T The unknown parameter to be estimated in the system; d k It is system noise with known distribution characteristics; u k The external excitation signal is the system input after being processed by the quantizer. Let r be the number of possible outputs of the quantizer, and let the possible output values ​​of the quantizer be μ1, μ2, ..., μ r , then u k ∈{μ1,μ2,…,μ r};π k =[u k ,…,u k-n+1 ] T It is a vector composed of system inputs.

[0078] At the same time, the FIR system outputs y k s is obtained through measurement using a multi-threshold quantizer with m thresholds. k , all y k The output vector is composed of all s k The measurement vector is formed by arranging the m threshold values ​​of the sensor from smallest to largest, denoted as C. w w = 1, 2, ..., m, and -∞ <C1<C2<…<C m If the value is less than ∞, the measurement process can be represented by a function as follows:

[0079]

[0080] s k The data is transmitted via a communication network to a remote estimation center for estimating the unknown system parameter θ. During communication transmission, to conserve channel resources, an event trigger is designed to determine s. k Whether to send, and set γ k The trigger condition is represented by ∈{0,1}, when γ k =1 indicates that the event trigger was successfully triggered, that is, the s signal at this moment was sent. k γ k Conversely, if γ = 0, then after this event-driven mechanism, the information received by the remote estimation center from the communication network is {γ}. k} and {γ k s k Therefore, the structural block diagram of the entire system is as follows: Figure 2 As shown.

[0081] Therefore, this application provides an event trigger to reduce the number of data transmissions without losing data information. Based on this, it further integrates the data available when the remote estimation center acts as the receiving end to design an algorithm for identifying the unknown parameter θ of the system, and discusses and analyzes the algorithm's convergence properties.

[0082] For the quantized input u of the system k The vector π formed k Since the quantization order of the quantizer is r, π is... k Let l be the number of permutations that appear in the input sequence, then l ≤ r n ,Right now:

[0083]

[0084] but

[0085] From the input sequence {u k The generated matrix is:

[0086]

[0087] Let N τ,k Indicates time k Each value ψ τ The frequency of occurrence of is defined as follows:

[0088]

[0089]

[0090] in,

[0091]

[0092] When the system input is At that time, s k There are a total of m+1 possible values. Therefore, by agreement, the sender and receiver can choose one of these values ​​not to send the data. In this case, the receiver still knows the value s at the corresponding time. k Value. For example, if s is selected. k =1 means no transmission, so for the receiver, γ k =0 means s k =1. Therefore, there is a problem: how to choose which s not to send. k What value can achieve a lower communication rate?

[0093] when When, assuming s is chosen k If j, j∈{0,1,…,m} is not sent, then we can obtain:

[0094]

[0095] From (7), it can be seen that when Pr(s) is selected... k =j) when s is at its maximum k By not sending the value, the minimum communication rate can be obtained. However, s k The probability of each value occurring is often unknown, but it can be determined by using s. k The frequency of each output is replaced by its probability, thus ensuring the feasibility of the event trigger.

[0096] Therefore, a counter is added at both the transmitting and receiving ends to count the l types of system inputs ψ up to time k. τ ,τ=1,…,l, s obtained after measurement by a multi-threshold quantizer k The frequency of each output is calculated. The statistical results from the transmitter's counter are then used... This means, that is:

[0097]

[0098] in,

[0099]

[0100] use This represents the statistics up to time k, for each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, that is:

[0101]

[0102] Since the receiver counter needs to wait until communication ends before synchronizing with the transmitter counter at time k, the event trigger at time k is calculated using only the data sample from time k-1. In this case, the designed event trigger can be represented as the following characteristic function:

[0103]

[0104] because Therefore, when extended to l types of system inputs, the designed event trigger can be expressed in the following function form:

[0105]

[0106] (11).

[0107] It should be noted that when k=1, Since all values ​​are 0, the initial value γ1 is specifically defined as 1.

[0108] Therefore, the data that the sending end needs to send is determined by s. k Change to γ k s k Meanwhile, because the receiver cannot directly use γ... k s k System identification calculations require processing the received data. The remote estimation center, acting as the data receiver, synchronizes the receiver's counter with the sender's counter and defines the corresponding parameters. Therefore, for time k, the receiver processes the data as follows:

[0109]

[0110]

[0111]

[0112] Among them, the initial value N τ,0 =0,

[0113] This completes the design of the event-driven (FCMQO-EC) communication mechanism for the multi-threshold quantization system, allowing for the subsequent use of the processed data. The data is used for system identification.

[0114] For the random variable sequence {d k} follows independent and identically distributed distributions, and its cumulative distribution function is F(·), which is invertible and F -1 (·) is its second-order continuously differentiable inverse function.

[0115] For π k Each value of ψ τ β exists τ >0 makes

[0116]

[0117] For ease of explanation, the following definition is provided:

[0118] F i (x)=F(C i -x) (15).

[0119] Since the parameter identification of the system described in the problem description requires the results of the multi-threshold measurement process (2), the designed FCMQO-EC communication mechanism needs to ensure that the information contained in the data is not damaged during the data transmission process, that is, the receiver can restore the statistical characteristics of the sender's data based on the actual received data. Therefore, the data recovery capability of the designed FCMQO-EC communication mechanism in the data processing process (12)-(14) at the receiver will be discussed below.

[0120] When k = 1, according to the designed event trigger, γ1 = 1, then from (12)-(14) we can... have to as well as

[0121]

[0122] When k = 2, from (12) and (16), we can obtain that when γ2 = 1, When γ2 = 0, we have

[0123]

[0124] Combining equation (11), it can be seen that only when When γ2 = 0, therefore when γ2 = 0, It still holds true. Then, combining (8) and (13), we get...

[0125]

[0126] Similarly, from (16) and (18), we can obtain

[0127]

[0128] It can be proved by mathematical induction that the conclusions of equations (17)-(19) still hold for k>2, that is, for k≥2, the following condition is satisfied. In summary, for any time k≥1, the following relationship holds:

[0129]

[0130] In summary, the designed FCMQO-EC communication mechanism does not affect the integrity of the transmitted data and can enable the receiving end to fully restore the data information of the sending end while reducing the communication rate.

[0131] For the event trigger of the designed FCMQO-EC communication mechanism, its communication rate is defined as follows:

[0132]

[0133] First, from (9) and (11), we can obtain

[0134]

[0135] in, Let d1, d2, ..., d k-1 The generated σ-algebra, i.e. Therefore, we can know therefore It is a martingale difference sequence.

[0136] because but

[0137]

[0138] From the martingale difference law of large numbers, we can obtain

[0139]

[0140] From (1), (2), and (8), we can obtain

[0141]

[0142] Similarly, we can obtain

[0143]

[0144] as well as

[0145]

[0146] From this we can obtain

[0147]

[0148] Therefore, from (26), we can obtain

[0149]

[0150] Combining (22) and (27), the communication rate of event trigger (11) is:

[0151]

[0152] Where F i (ψ τ θ) is given by (15).

[0153] Based on the data processing (12)-(14) performed at the receiving end, the corresponding identification algorithm is designed as follows:

[0154]

[0155]

[0156] Where {υ r Let {r = 1, ..., m} be m weights, and satisfy the following conditions:

[0157] Since the relationship shown in equation (20) is satisfied at any time k≥1, it is proven that the designed event-driven communication mechanism does not affect the integrity of the transmitted data. Subsequently, the parameter estimates obtained by the receiver through the joint operation of algorithms (12)-(14) and (29)-(30) can be obtained. It strongly converges to θ, that is:

[0158]

[0159] Simultaneous parameter estimates It has the following asymptotic normality:

[0160]

[0161] And the mean square convergence rate is:

[0162]

[0163] Where H1=diag[β1,…,β l ], And γ=[υ1,…,υ m ] T U(·) and P(·) are given by equations (34) and (35) respectively. This indicates convergence according to the distribution.

[0164]

[0165]

[0166] Among them, F i (x) is given by (15), and diag[…] denotes a diagonal matrix.

[0167] The method provided in this application is simulated below.

[0168] Consider the following system:

[0169]

[0170] The true values ​​of the unknown system parameters are set to θ = [3, -1]. T System noise {d k Let} be a random normally distributed noise sequence with a mean of 0 and a variance of 5. The quantization results of the external excitation input are set as two types: [1] and [3]. Therefore, π k The possible values ​​are [1, 1]. T [1,3] T [3,1] T [3,3] T Four scenarios. The system output y... k Two quantization thresholds are set, C1 = -1 and C2 = 1, and the measurement results are expressed as follows:

[0171]

[0172] The above system uses the FCMQO-EC communication mechanism, and its communication rate simulation results are as follows: Figure 3 As shown.

[0173] For the receiving end, a joint operation of algorithms (12)-(14) and (29)-(30) is used, and the identification weights {υ1=0.55,υ2=0.45} are set to obtain the identification convergence results of the unknown parameters of the system as follows: Figure 4 As shown, when k is sufficiently large, the algorithm's identification result... It converges to the true value of the parameter θ. Simultaneously, plot the results separately. The probability distribution histogram of the results of 1000 operations on two components is shown below. Figure 5 As shown, where σ 11 , σ 22 (32) of which (Φ) T H1Φ) -1 Φ T H2Φ(Φ T H1Φ) -1 The main diagonal elements of the matrix were calculated according to the experimental conditions. In summary, the experimental results show that the designed FCMQO-EC communication mechanism does not affect the integrity of the information contained in the transmitted data, and the identification results satisfy the convergence expressed by equation (31) and the asymptotic normality expressed by equation (32).

[0174] On the other hand, such as Figure 6As shown, an event-driven communication device for a multi-threshold quantization system is also provided. This device is used to implement the event-driven communication method for the multi-threshold quantization system provided in this embodiment of the invention. The device includes:

[0175] Acquisition module 601 is used to acquire the input vector of the FIR system;

[0176] Measurement module 602 is used to obtain a measurement vector by measuring a multi-threshold quantizer with m thresholds after obtaining an output vector through the FIR system based on the input vector.

[0177] The estimation module 603 is used to dynamically adjust the trigger reference value of the event trigger based on the data frequency of the completed transmission using measurement vectors independently statistically counted by both the sender and receiver. It obtains a trigger state value by comparing the measurement vector with the reference value, and generates a transmission value by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center via a communication network, whereby the remote estimation center estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is:

[0178] in, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

[0179] On the other hand, an event-driven communication device for a multi-threshold quantization system is also provided, the event-driven communication device for the multi-threshold quantization system comprising:

[0180] processor;

[0181] A memory storing computer-readable instructions, which, when executed by the processor, implement the method provided in the embodiments of the present invention.

[0182] On the other hand, a computer-readable storage medium is also provided, wherein program code is stored in the computer-readable storage medium, and the program code can be called by a processor to execute the method provided in the embodiments of the present invention. The beneficial effects brought about by the technical solution provided in the embodiments of the present invention include at least the following:

[0183] This invention, through statistical analysis of the frequency of data occurrence at the sending and receiving ends, dynamically selects non-critical data to suppress transmission, thereby reducing the number of communications while ensuring data integrity without increasing additional computation or feedback communication.

[0184] This application designs a multi-threshold quantized observation FCMQO-EC communication mechanism based on frequency statistics, effectively reducing the number of communications and ensuring data integrity, while also deriving its communication rate. Based on the quantized observation results and system noise statistics, an algorithm for identifying unknown parameters of the FIR system is proposed, and its convergence performance is verified.

[0185] Figure 7 This is a schematic diagram of the structure of an event-driven communication device for a multi-threshold quantization system provided in an embodiment of the present invention, as shown below. Figure 7 As shown, optionally, the event-driven communication device 710 of the multi-threshold quantization system may include a first processor 2001.

[0186] Optionally, the event-driven communication device 710 of the multi-threshold quantization system may also include a memory 2002 and a transceiver 2003.

[0187] The first processor 2001, memory 2002, and transceiver 2003 can be connected via a communication bus.

[0188] The following is combined with Figure 7 The following is a detailed description of each component of the event-driven communication device 710 for the multi-threshold quantization system:

[0189] The first processor 2001 is the control center of the event-driven communication device 710 of the multi-threshold quantization system. It can be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 can be one or more central processing units (CPUs), application-specific integrated circuits (ASICs), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0190] Optionally, the first processor 2001 can execute various functions of the event-driven communication device 710 of the multi-threshold quantization system by running or executing software programs stored in the memory 2002 and calling data stored in the memory 2002.

[0191] In a specific implementation, as one example, the first processor 2001 may include one or more CPUs, for example... Figure 7 CPU0 and CPU1 are shown in the diagram.

[0192] In a specific implementation, as one example, the event-driven communication device 710 of the multi-threshold quantization system may also include multiple processors, for example... Figure 7 The first processor 2001 and the second processor 2004 are shown in the diagram. Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). Here, "processor" can refer to one or more devices, circuits, and / or processing cores used to process data (e.g., computer program instructions).

[0193] The memory 2002 is used to store the software program that executes the present invention, and is controlled by the first processor 2001 to execute it. The specific implementation method can be referred to the above method embodiment, and will not be repeated here.

[0194] Optionally, the memory 2002 may be a read-only memory (ROM) or other type of static storage device capable of storing static information and instructions, random access memory (RAM) or other type of dynamic storage device capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory 2002 may be integrated with the first processor 2001 or may exist independently, and may be communicated via the interface circuit of the event-driven communication device 710 of the multi-threshold quantization system. Figure 7 (Not shown in the figure) is coupled to the first processor 2001, and the embodiments of the present invention do not specifically limit this.

[0195] The transceiver 2003 is used to communicate with network devices or with terminal devices.

[0196] Alternatively, transceiver 2003 may include a receiver and a transmitter. Figure 7 (Not shown separately). The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0197] Optionally, the transceiver 2003 can be integrated with the first processor 2001 or exist independently, and can be connected to the interface circuit of the event-driven communication device 710 of the multi-threshold quantization system. Figure 7 (Not shown in the figure) is coupled to the first processor 2001, and the embodiments of the present invention do not specifically limit this.

[0198] It should be noted that, Figure 7 The structure of the event-driven communication device 710 of the multi-threshold quantization system shown does not constitute a limitation on the router. Actual knowledge structure identification devices may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0199] Furthermore, the technical effect of the event-driven communication device 710 of the multi-threshold quantization system can be referred to the technical effect of the multimodal emotion recognition method described in the above method embodiments, and will not be repeated here.

[0200] It should be understood that the first processor 2001 in this embodiment of the invention may be a central processing unit (CPU), or it may be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0201] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDR SDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0202] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. 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, motor drive, or data center to another website, computer, motor drive, or data center via infrared, microwave, or other means. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a motor drive or data center that includes one or more sets of available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium. A semiconductor medium can be a solid-state drive.

[0203] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0204] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0205] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0206] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0207] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, apparatuses, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0208] In the several embodiments provided by this invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another device, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0209] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0210] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0211] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, a motor driver, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0212] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. An event-driven communication method for a multi-threshold quantization system, characterized in that, include: Obtain the input vector of the FIR system; Based on the input vector, after obtaining the output vector through the FIR system, the measurement vector is obtained by measuring through a multi-threshold quantizer with m thresholds; The frequency of data transmission is determined by independently statistically analyzed measurement vectors from both the sender and receiver. The trigger reference value is dynamically adjusted, and a trigger state value is obtained by comparing the measurement vector with the reference value. The transmission value is generated by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center via a communication network. The remote estimation center then estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is: in, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

2. The method according to claim 1, characterized in that, The remote estimation center processes the received data using Formula 2, which is: in, Used to estimate the unknown parameters of the FIR system, initial values N τ,0 =0, 3. The method according to claim 1, characterized in that, The FIR system is a single-input single-output finite impulse response system. Where θ=[a1,…,a n ] T The unknown parameter to be estimated in the system; d k It is system noise with known distribution characteristics; u k The external excitation signal is the system input after being processed by the quantizer. Let r be the number of possible outputs of the quantizer, and let the possible output values ​​of the quantizer be μ1, μ2, ..., μ r , then u k ∈{μ1,μ2,…,μ r };π k =[u k ,…,u k-n+1 ] T It is a vector composed of system inputs.

4. The method according to claim 2, characterized in that, The value y in the output vector of the FIR system k The value s in the measurement vector is obtained through a multi-threshold quantizer with m thresholds. k Arrange the m thresholds of the quantizer in ascending order, and denote them as C. w w = 1, 2, ..., m, and -∞ <C1<C2<…<C m If the value is less than ∞, the measurement process can be represented by a function as follows:

5. The method according to claim 1, characterized in that, The event trigger value includes 1 and 0. When the event trigger value is 1, the measurement vector value is sent; when the event trigger value is 0, the measurement vector value is not sent.

6. The method according to claim 4, characterized in that, The estimation of unknown parameters of the FIR system by the remote estimation center based on the transmitted values ​​includes: The unknown parameters of the FIR system are estimated using Formula 3, which includes: Where {υ r Let {r = 1, ..., m} be m weights, and satisfy the following conditions: F i (x)=F(C i -x).

7. The method according to claim 6, characterized in that, The parameter estimate It converges strongly to θ.

8. An event-driven communication device for a multi-threshold quantization system, wherein the event-driven communication device for the multi-threshold quantization system is used to implement the event-driven communication method for the multi-threshold quantization system as described in any one of claims 1-7, characterized in that, The device includes: The acquisition module is used to acquire the input vector of the FIR system; The measurement module is used to obtain a measurement vector by measuring a multi-threshold quantizer with m thresholds after obtaining an output vector through the FIR system based on the input vector. The estimation module dynamically adjusts the trigger reference value of the event trigger based on the data transmission frequency of the measurement vector independently statistically analyzed by both the sender and receiver. It obtains the trigger state value by comparing the measurement vector with the reference value, and generates the transmission value by multiplying the trigger state value with the measurement vector. The sender is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center via a communication network, where the remote estimation center estimates the unknown parameters of the FIR system based on the transmission value. The event trigger is represented by Formula 1, which is: in, This indicates that the statistics are up to time k, ψ τ s is the system input value in the input vector. k For the values ​​in the measurement vector, each system input ψ τ Corresponding to s k The most frequently occurring s in the output k Value, π k For the input vector, k is the statistical cutoff time, l is π k The number of permutations that appear in the input sequence, l≤r n r is the quantization order of the quantizer, and the initial value is γ1 = 1.

9. An event-driven communication device for a multi-threshold quantization system, characterized in that, The event-driven communication device of the multi-threshold quantization system includes: processor; A memory storing computer-readable instructions that, when executed by the processor, implement the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium contains program code that can be invoked by a processor to execute the method as described in any one of claims 1 to 7.

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