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

Abstract

The invention provides an event-driven communication method and device for a multi-threshold quantization system, and relates to the technical field of communication, and the method comprises the steps: obtaining an input vector of an FIR (Finite Impulse Response) system; according to the input vector, after an output vector is obtained through an FIR system, a measurement vector is obtained through measurement of a multi-threshold quantizer with m thresholds; the method comprises the following steps: dynamically adjusting a trigger reference value of an event trigger according to the data frequency of which the transmission of a measurement vector is completed and which is independently counted by a transmitter and a receiver, obtaining a trigger state value according to a comparison result of the measurement vector and the reference value, and generating a transmission value after multiplying the trigger state value by the measurement vector, wherein the transmitter of the transmitter and the receiver is a multi-threshold quantizer; the receiver is a far-end estimation center, and the far-end estimation center estimates unknown parameters of the FIR system according to the sending value. According to the embodiment of the invention, on the premise of not increasing additional calculation and feedback communication, the data integrity is ensured while the communication times are reduced.

Description

Technical Field

[0001] The present invention relates to the field of communication technologies, and particularly to an event-driven communication method and apparatus for a multi-threshold quantization system. Background Art

[0002] With the rapid development of computer and network communication technologies, traditional control systems are limited by localized control and decision-making and have gradually been unable to meet the requirements of complex real-world applications. Networked Control Systems (NCSs) connect nodes through a shared network and use network technologies to achieve remote distributed control and decision-making, significantly improving system efficiency and flexibility. Therefore, NCSs have become an important research direction. Currently, NCSs are widely applied in fields such as transportation systems, power systems, and microgrids. A Finite Impulse Response (FIR) system is a common networked control system. However, the continuous increase in subsystems and the proliferation of their corresponding devices and sensors have led to an exponential growth in data transmission volume. How to optimize transmission to save channel resources, reduce bandwidth occupancy, and effectively transmit data to the estimation center has become an urgent problem to be solved.

[0003] Under this demand, quantifying the transmitted data is one direction. At the same time, due to the accuracy and cost limitations of some sensors, their outputs are also quantified. However, the information loss caused during the quantization process also increases the difficulty of the identification work. Therefore, research on system identification based on quantized observations has also received extensive attention. In addition, in terms of how to save communication resources, the event-driven mechanism is also an effective method, attracting the attention of a large number of scholars and achieving many excellent results.

[0004] The identification of an FIR system under the combined influence of multi-threshold quantization and the event-driven mechanism. Since quantization loses the information content of the data and the event-driven mechanism destroys the integrity of the measurement information, the coupling of the two also results in a high degree of nonlinearity of the system, greatly increasing the difficulty of system parameter identification. Summary of the Invention

[0005] To solve the technical problem of the relatively high difficulty in parameter identification of the FIR system in the prior art, embodiments of the present invention provide 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] After obtaining an output vector through the FIR system according to the input vector, a measurement vector is obtained through measurement by a multi-threshold quantizer having m thresholds;

[0009] The frequency of data transmission completed by the measurement vector independently counted by the sender and the receiver is used to dynamically adjust the event trigger trigger reference value, and the trigger state value is obtained by comparing the measurement vector with the reference value. After multiplying the trigger state value with the measurement vector, a transmission value is generated, wherein the sender of the sender and the receiver is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center through a communication network, and the remote estimation center estimates the unknown parameters of the FIR system according to the transmission value, wherein the event trigger is represented by Formula 1, and Formula 1 is:

[0010] 3. represents statistics up to time k, ψ τ is the system input value in the input vector, s k For the values in the measurement vector, each system input ψ τ Corresponding k Output the s with the highest frequency k Value, π k is the input vector, k is the statistical cutoff time, l is π k The number of permutations that occur in the input sequence, l≤r n , r is the quantization order of the quantizer, and the initial value γ1=1.

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

[0012]

[0013]

[0014]

[0015] in, Used to estimate the unknown parameters of the FIR system, the initial value 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 are the unknown parameters to be estimated by the system; d k is the system noise with known distribution characteristics; u k is the system input after the external excitation signal is processed by the quantizer. Suppose the possible number of outputs of the quantizer is r, and the possible output values of the quantizer are denoted as μ1, μ2, …, μ r , then u k ∈ {μ1, μ2, …, μ r}; π k = [u k , …, u k-n+1 T is the vector composed of system inputs.

[0019] Optionally, the value y k in the output vector of the FIR system is measured by a multi-threshold quantizer with m thresholds to obtain the value s k in the measurement vector. The m thresholds of the sensor are arranged in ascending order and denoted as C w , w = 1, 2, …, m, and -∞ < C1 < C2 < … < C m < ∞. Then the measurement process is represented by a function as:

[0020]

[0021] Optionally, the values of the event trigger include 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 remote estimation center estimates the unknown parameters of the FIR system according to the sent value, including:

[0023] Estimating the unknown parameters of the FIR system through Formula 3, and the Formula 3 includes:

[0024]

[0025]

[0026] where {υ r , r = 1, …, m} are m set weights and satisfy F i (x) = F(C i - x).

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

[0028] ​​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 is used to implement the event-driven communication method for the multi-threshold quantization system provided by the embodiments of the present invention. The device includes:

[0029] An acquisition module, configured to acquire an input vector of the FIR system;

[0030] A measurement module, configured to obtain an output vector through the FIR system according to the input vector, and then obtain a measurement vector through measurement by a multi-threshold quantizer with m thresholds;

[0031] An estimation module, configured to dynamically adjust the trigger reference value of the event trigger by the frequency of the data that has been sent in the measurement vectors independently statistically by both the transmitter and the receiver, obtain a trigger status value through the comparison result between the measurement vector and the reference value, generate a transmission value after multiplying the trigger status value by the measurement vector, where the transmitter of both the transmitter and the receiver is the multi-threshold quantizer, and the receiver is the remote estimation center. The transmission value is transmitted to the remote estimation center through the communication network, and the remote estimation center estimates the unknown parameters of the FIR system according to the transmission value. Among them, the event trigger is represented by Formula 1, and Formula 1 is:

[0032] Wherein, represents the system input value in the input vector up to the k-th moment, ψ τ is the system input value in the input vector, s k is the value in the measurement vector. For each system input ψ τ corresponding to s k the s k value with the highest output occurrence frequency, π k is the input vector, k is the statistical cut-off moment, l is the number of permutation cases of π k appearing in the input sequence, l ≤ r n , r is the quantization order of the quantizer, and the initial value 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 includes:

[0034] A processor;

[0035] A memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, the method provided by the embodiments of the present invention is implemented.

[0036] On the other hand, a computer-readable storage medium is also provided. 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 by the embodiments of the present invention. The beneficial effects brought by the technical solutions provided by the embodiments of the present invention at least include:

[0037] By counting the occurrence frequencies of data at the sending end and the receiving end, the embodiments of the present invention dynamically select non-critical data for suppression of transmission, reducing the number of communications while ensuring data integrity without adding extra calculations and feedback communications. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

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

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

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

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

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

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

[0045] Figure 7 is a schematic structural diagram of an event-driven communication device for a multi-threshold quantization system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0046] The following describes the technical solutions in the present invention with reference to the drawings.

[0047] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0048] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0049] In the embodiments of the present invention, sometimes a subscript such as W1 may be mistakenly written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are consistent.

[0050] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0051] In order to solve the technical problem of high difficulty in parameter identification of FIR system in the prior art, the embodiment of the present invention provides an event-driven communication method and device for a multi-threshold quantization system. The technical solution is as follows:

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

[0053] S1, obtaining an input vector of the FIR system;

[0054] S2. After obtaining an output vector through the FIR system according to the input vector, a measurement vector is obtained through measurement by a multi-threshold quantizer having m thresholds;

[0055] S3, dynamically adjust the event trigger trigger reference value according to the frequency of data sent by the measurement vector independently counted by the sender and receiver, obtain the trigger state value by comparing the measurement vector with the reference value, and generate the sending value by multiplying the trigger state value with the measurement vector, wherein the sender of the sender and receiver is a multi-threshold quantizer, and the receiver is a remote estimation center, and the sending value is transmitted to the remote estimation center through the communication network, and the remote estimation center estimates the unknown parameters of the FIR system according to the sending value, wherein the event trigger is represented by Formula 1, and Formula 1 is:

[0056] Among them, represents the statistics up to the k-th moment, ψ τ is the system input value in the input vector, s k is the value in the measurement vector, and each system input ψ τ corresponds to s k outputs the s k value with the highest occurrence frequency, π k is the input vector, k is the statistical cut-off moment, l is the number of permutation cases where π k appears in the input sequence, l ≤ r n , and r is the quantization order of the quantizer, with the initial value γ1 = 1.

[0057] Optionally, the remote estimation center processes the received data through Equation 2, and Equation 2 is:

[0058]

[0059]

[0060]

[0061] Among them, is used to estimate the unknown parameters of the FIR system, with the initial value N τ,0 = 0,

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

[0063]

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

[0065] Optionally, the value y in the output vector of the FIR system k is measured by a multi-threshold quantizer with m thresholds to obtain the value s in the measurement vector k . Arrange the m thresholds of the sensor in ascending order and denote them as C w , w = 1, 2, …, m, and -∞ < C1 < C2 < … < C m < ∞. Then the measurement process is represented by a function as follows:

[0066]

[0067] Optionally, the values of the event trigger include 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 remote estimation center estimates the unknown parameters of the FIR system according to the sent value, including:

[0069] Estimate the unknown parameters of the FIR system through Formula 3, and the Formula 3 includes:

[0070]

[0071]

[0072] where {υ r , r = 1, …, m} are m set weights and satisfy F i (x) = F(C i - x).

[0073] Optionally, the parameter estimation value strongly converges to θ.

[0074] This application considers the identification of FIR systems under the combined influence of multi-threshold quantization and event-driven mechanisms. Since quantization loses the information content of data and the event-driven mechanism destroys the integrity of measurement information, the coupling of the two also causes a high degree of non-linearity in the system, greatly 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 outputs for the case of multi-threshold quantization observations, which can obtain fewer communication times while retaining the integrity of information as much as possible. At the same time, under the condition of quantized input, an unknown parameter identification algorithm for FIR systems based on the empirical measure method 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 are the unknown parameters to be estimated of the system; d k is the system noise with known distribution characteristics; u k is the system input after the external excitation signal is processed by the quantizer. Suppose the possible number of outputs of the quantizer is r, and the possible output values of the quantizer are denoted as μ1, μ2, …, μ r , then u k ∈{μ1, μ2, …, μ r}; π k = [u k , …, u k-n+1 T is the vector composed of system inputs.

[0078] Meanwhile, the output y k of the FIR system is measured by a multi-threshold quantizer with m thresholds to obtain s k . All y k constitute the output vector, and all s k constitute the measurement vector. Arrange the m thresholds of this sensor in ascending order, and denote them as C w , w = 1, 2, …, m, and -∞ < C1 < C2 < … < C m < ∞, then the measurement process can be expressed by a function as:

[0079]

[0080] ​​s k It is transmitted to the remote estimation center through a communication network for estimating the unknown parameter θ of the system. During the communication transmission process, in order to save channel resources, an event trigger is designed to determine whether s k is to be sent, and let γ k ∈{0, 1} represent the trigger situation of the trigger. When γ k = 1, it means that the event trigger is successfully triggered, that is, s at this moment is sent k , and vice versa when γ k = 0. Then after this event-driven mechanism link, the information received by the remote estimation center from the communication network is {γ k} and {γ k s k}. Thus, the structural block diagram of the entire system is as shown in Figure 2 .

[0081] Therefore, this application provides an event trigger to achieve the goal of reducing the number of data transmissions without losing the information of the data. On this basis, further synthesize the data situation that can be obtained when the remote estimation center is the receiving end to design an identification algorithm for the unknown parameter θ of the system, and discuss and analyze the convergence properties of its algorithm.

[0082] For the vector π k composed of the quantized input u k of the system, since the quantization order of the quantizer is r, the number of permutation situations of π k appearing in the input sequence is denoted as l, then l ≤ r n , that is:

[0083]

[0084] Then

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

[0086]

[0087] Let N τ,k represent the number of occurrences of each value ψ up to the k-th moment τ , and its definition is as follows:

[0088]

[0089]

[0090] Among them,

[0091]

[0092] When the system input is , s k has a total of m + 1 values. Therefore, through an agreement between the sender and the receiver, one of the values is selected not to be sent. At this time, the receiver still knows the value of s at the corresponding moment. k Value. For example, if it is selected that s k = 1 is not sent, then for the receiver, γ k = 0 means that s k = 1. Therefore, there is a problem, that is: how to select the value of s that is not sent to obtain a smaller communication rate? k

[0093] When , assuming that it is selected that s k = j, j ∈ {0, 1,..., m} is not sent, then it can be obtained that:

[0094]

[0095] As can be seen from (7), when the value of s corresponding to the maximum Pr(s k = j) is not sent, the minimum communication rate can be obtained. However, the occurrence probability of each value of s is often unknown, but the frequency of occurrence of each output of s can be used to replace its probability to ensure the realizability of the event trigger. k k k

[0096] Therefore, a counter is added at the sender and the receiver respectively to count the frequency of occurrence of each output of s measured by the multi-threshold quantizer for the corresponding l system inputs ψ τ , τ = 1,..., l up to time k. And the statistical result of the counter at the sender is represented by k , that is:

[0097]

[0098] Among them,

[0099]

[0100] Use to represent the value of s with the highest frequency of occurrence of the output corresponding to each system input ψ τ up to time k, that is: k k , that is:

[0101]

[0102] Since the receiver counter needs to be synchronized with the sender counter after the communication ends at time k, the event trigger at time k is calculated using only the data samples at time k - 1. That is, when the designed event trigger can be expressed as the following indicator function:

[0103]

[0104] Because When extended to l system inputs, the designed event trigger can be expressed in the following functional form:

[0105]

[0106] (11).

[0107] Note that when k = 1, are all 0, so the initial value γ1 = 1 is specially defined.

[0108] Thus, the data to be sent by the sender is changed from s k to γ k s k . At the same time, since the receiver cannot directly use γ k s k for system identification operations, the received data needs to be processed. The remote estimation center, as the data receiver, synchronizes the receiver counter with the sender counter and defines accordingly Therefore, for the k-th moment, the receiver processes the data as follows:

[0109]

[0110]

[0111]

[0112] where the initial value N τ,0 = 0,

[0113] So far, the design of the event-driven (FCMQO-EC) communication mechanism for the multi-threshold quantization system is completed, and the processed data can be used for system identification work.

[0114] For the sequence of random variables {d k} that follows independent and identical distribution, its cumulative distribution function is F(·), F(·) is invertible and F -1 (·) is its second-order continuously differentiable inverse function.

[0115] For each value result ψ of π k τ τ there exists β τ > 0 such that

[0116]

[0117] For convenience of description, define:

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

[0119] Since the parameter identification of the system in the problem description requires the result of the multi - threshold measurement process (2), for the designed FCMQO - EC communication mechanism, it is necessary to ensure that the information contained in the data is not damaged during the data transmission process, that is, the receiving end can restore the statistical characteristics of the data at the sending end according to the actually received data. Therefore, the data restoration ability of the designed FCMQO - EC communication mechanism in the data processing process (12)-(14) at the receiving end will be discussed below.

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

[0121]

[0122] When k = 2, from (12) and (16), it can be obtained that when γ2 = 1,[[]] when γ2 = 0, there is

[0123]

[0124] Combined with equation (11), it can be seen that only when γ2 = 0, so when γ2 = 0, still holds. Then combined with (8), (13), we can get

[0125]

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

[0127]

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

[0129]

[0130] As can be seen above, the designed FCMQO-EC communication mechanism does not affect the integrity of the transmitted data, and can enable the receiving end to completely 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, define its communication rate as

[0132]

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

[0134]

[0135] where, is the σ-algebra generated by d1, d2, …, d k-1 that is, From this, we can know that Therefore is a martingale difference sequence.

[0136] Because then

[0137]

[0138] By the law of large numbers for martingale differences, we can get

[0139]

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

[0141]

[0142] Similarly, we can get

[0143]

[0144] and

[0145]

[0146] From this, we can get

[0147]

[0148] From this, from (26), we can get

[0149]

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

[0151]

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

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

[0154]

[0155]

[0156] where {υ r , r = 1, …, m} are m set weight values and satisfy

[0157] Since the relationship shown in equation (20) is satisfied for any moment of k ≥ 1. It is proved that the designed event-driven communication mechanism does not affect the integrity of the transmitted data. Then the parameter estimation value obtained by the combined operation of the algorithms (12)-(14) and (29)-(30) at the receiving end strongly converges to θ, that is:

[0158]

[0159] Meanwhile, the parameter estimation value 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(·), P(·) are given by equations (34) and (35) respectively, denotes convergence in distribution.

[0164]

[0165]

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

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

[0168] Consider a system as follows:

[0169]

[0170] Among them, the true value of the system unknown parameter is set to θ = [3, -1] T , the system noise {d k} is set as a random normal distribution noise sequence with a mean of 0 and a variance of 5. The quantization results of the external excitation input are set to [1] and [3], so that the value of π k has [1, 1] T , [1, 3] T , [3, 1] T , [3, 3] T four cases. For the system output y k two quantization thresholds are set, which are C1 = -1 and C2 = 1 respectively, and the measurement results are expressed as:

[0171]

[0172] The FCMQO-EC communication mechanism is adopted for the above system, and the simulation results of its communication rate are as Figure 3 shown.

[0173] For the receiving end, the joint operation of algorithms (12)-(14) and (29)-(30) is adopted, and the identification weight {υ1 = 0.55, υ2 = 0.45} is set. The identification convergence results of the system unknown parameters are as Figure 4 shown. It can be seen that when k is large enough, the algorithm identification result converges to the parameter true value θ. At the same time, the probability distribution histograms of the 1000 operation results of the two components are plotted respectively, as shown, where σ Figure 5 , σ 11 , σ 22 are the main diagonal elements of the matrix calculated according to the experimental conditions in (32) (Φ T H1Φ) -1 Φ T H2Φ(Φ T H1Φ) -1 respectively. In summary, the experimental results prove that the designed FCMQO-EC communication mechanism does not affect the integrity of the information contained in the transmitted data, and at the same time, the identification results satisfy the convergence expressed by formula (31) and the asymptotic normality expressed by formula (32).

[0174] On the other hand, as Figure 6As shown, 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 is used to implement the event-driven communication method of the multi-threshold quantization system provided in the embodiments of the present invention. The device includes:

[0175] An acquisition module 601, configured to acquire the input vector of the FIR system;

[0176] A measurement module 602, configured to obtain an output vector through the FIR system according to the input vector, and then obtain a measurement vector through measurement by a multi-threshold quantizer with m thresholds;

[0177] An estimation module 603, configured to dynamically adjust the triggering reference value of the event trigger by the frequency of the data that has been transmitted in the measurement vectors independently statistically by both the transmitter and the receiver, obtain a trigger status value through the comparison result between the measurement vector and the reference value, generate a transmission value after multiplying the trigger status value by the measurement vector, where the transmitter of both the transmitter and the receiver is a multi-threshold quantizer, and the receiver is a remote estimation center. The transmission value is transmitted to the remote estimation center through a communication network, and the remote estimation center estimates the unknown parameters of the FIR system according to the transmission value. Among them, the event trigger is represented by Formula 1, and Formula 1 is:

[0178] Among them, represents the system input value in the input vector up to the k-th moment, ψ τ is the system input value in the input vector, s k is the value in the measurement vector. For each system input ψ τ corresponding to s k with the highest occurrence frequency of the output, π k is the input vector, k k is the statistical cut-off moment, l is the number of permutation cases of π appearing in the input sequence, l ≤ r k , r is the quantization order of the quantizer, and the initial value γ1 = 1. n

[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 includes:

[0180] A processor;

[0181] A memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, the method provided in the embodiments of the present invention is implemented.

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

[0183] By counting the occurrence frequencies of data at the sending end and the receiving end, the embodiments of the present invention dynamically select non-critical data for suppression of transmission, reducing the number of communications while ensuring data integrity without adding additional calculations and feedback communications.

[0184] This application designs a FCMQO-EC communication mechanism with multi-threshold quantization observation based on the frequency statistics results, effectively reducing the number of communications and ensuring data integrity, and deducing its communication rate at the same time. An identification algorithm for unknown parameters of the FIR system is proposed based on the quantization observation results and the statistical characteristics of system noise, and its convergence performance is verified.

[0185] Figure 7 FIG. is a schematic structural diagram of an event-driven communication device of a multi-threshold quantization system provided by the embodiments of the present invention. As Figure 7 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 further include a memory 2002 and a transceiver 2003.

[0187] Among them, the first processor 2001, the memory 2002, and the transceiver 2003 may be connected through a communication bus, for example.

[0188] Next, in combination with Figure 7 each component of the event-driven communication device 710 of the multi-threshold quantization system will be specifically introduced:

[0189] Among them, the first processor 2001 is the control center of the event-driven communication device 710 of the multi-threshold quantization system, which may be a single processor or a collective term for multiple processing elements. For example, the first processor 2001 is one or more central processing units (CPUs), or may be an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the 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 invoking data stored in the memory 2002.

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

[0192] In a specific implementation, as an example, the event-driven communication device 710 of the multi-threshold quantization system may also include multiple processors, such as Figure 7 the first processor 2001 and the second processor 2004 shown in

[0193] Among them, the memory 2002 is used to store the software program for executing the solution of the present invention and is controlled by the first processor 2001 for execution. The specific implementation method can refer to the above method embodiments and will not be elaborated here.

[0194] Optionally, the memory 2002 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, or an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CD-ROM), or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital versatile discs, Blu-ray discs, etc.), magnetic disk storage media, or any other medium that can be used to carry or store the desired program code in the form of instructions or data structures and can be accessed by a computer, but is not limited thereto. The memory 2002 can be integrated with the first processor 2001 or exist independently and is coupled to the first processor 2001 through the interface circuit ( Figure 7 not shown in

[0195] A transceiver 2003 for communicating with a network device or a terminal device.

[0196] Optionally, the 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 transmitting function.

[0197] Optionally, the transceiver 2003 may be integrated with the first processor 2001, or may exist independently, and is coupled to the first processor 2001 through an interface circuit ( Figure 7 not shown) of the event-driven communication device 710 of the multi-threshold quantization system. The embodiments of the present invention do not make specific limitations on 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. The actual knowledge structure recognition device may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0199] In addition, the technical effects of the event-driven communication device 710 of the multi-threshold quantization system may refer to the technical effects of the multi-modal emotion recognition method described in the above method embodiments, and will not be elaborated here.

[0200] It should be understood that the first processor 2001 in the embodiments of the present invention may be a central processing unit (CPU), and the processor may also 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 the processor may also be any conventional processor, etc.

[0201] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), or a flash memory. The volatile memory may be a 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 SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchlink 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 arbitrary combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present invention are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, motor driver, or data center to another website, computer, motor driver, or data center by means of infrared, microwave, etc. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a motor driver or a data center that contains one or more collections of available media. The available media can be magnetic media (such as floppy disks, hard disks, magnetic tapes), optical media (such as DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0203] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context before and after.

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

[0205] It should be understood that in various embodiments of the present invention, the magnitudes of the serial numbers of the above processes do not mean the sequence of execution. The execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0206] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

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

[0208] In several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

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

[0210] In addition, the functional units in each embodiment of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0211] When the above-mentioned functions are implemented in the form of 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, in essence, or the part that contributes to the prior art, or a part of this 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 for causing 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 various embodiments of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs.

[0212] As described above, the above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An event-driven communication method for a multi-threshold quantization system, characterized in that Including: Obtain the input vector of the FIR system; After obtaining the output vector through the FIR system according to the input vector, obtain the measurement vector through the measurement of a multi-threshold quantizer with m thresholds; Dynamically adjust the trigger reference value of the event trigger through the data frequency of the measurement vector that has been sent independently by both the transmitter and the receiver. Obtain the trigger status value through the comparison result between the measurement vector and the reference value. After multiplying the trigger status value by the measurement vector, generate the transmission value. Among them, the transmitter of both the transmitter and the receiver is a multi-threshold quantizer, and the receiver is a remote estimation center. Transmit the transmission value to the remote estimation center through the communication network. The remote estimation center estimates the unknown parameters of the FIR system according to the transmission value. Among them, the event trigger is represented by Formula 1, and the Formula 1 is: Among them, represents the statistics up to the k-th moment, ψ τ is the system input value in the input vector, s k is the value in the measurement vector, and each system input ψ τ corresponds to s k outputs the s value with the highest occurrence frequency k value, π k is the input vector, k is the statistical cut-off moment, l is the number of permutation cases where π k appears in the input sequence, l ≤ r n , r is the quantization order of the quantizer, and the initial value γ1 = 1.

2. The method according to claim 1, characterized in that, The remote estimation center processes the received data through Formula 2, and the Formula 2 is: Among them, used to estimate the unknown parameters of the FIR system, with an initial value N τ,0 = 0, 3. The method according to claim 1, wherein The FIR system is a single-input single-output finite impulse response system: where, θ = [a1, …, a n T are the unknown parameters to be estimated by the system; d k is the system noise with known distribution characteristics; u k is the system input after the external excitation signal is processed by the quantizer. Suppose the possible number of outputs of the quantizer is r, and the possible output values of the quantizer are denoted as μ1, μ2, …, μ r , then u k ∈ {μ1, μ2, …, μ r}; π k = [u k , …, u k-n+1 T is the vector composed of system inputs.​​ 4. The method according to claim 2, wherein The value y in the output vector of the FIR system k is measured by a multi-threshold quantizer with m thresholds to obtain the value s in the measurement vector k . The m thresholds of the sensor are arranged in ascending order and denoted as C w, where w = 1, 2, …, m, and -∞ < C1 < C2 < … < C m < ∞. Then the measurement process is represented by the function as follows:

5. The method according to claim 1, wherein The value of the event trigger includes 1 and 0. When the value of the event trigger is 1, send the value of the measurement vector. When the value of the event trigger is 0, do not send the value of the measurement vector.

6. The method according to claim 4, wherein The remote estimation center estimates the unknown parameters of the FIR system according to the transmission value, including: Estimate the unknown parameters of the FIR system through Formula 3, and the Formula 3 includes: where {υ r , r = 1, …, m} are m set weights and satisfy F i (x) = F(C i -x).

7. The method according to claim 6, characterized in that, The estimated value of the parameter strongly converges to θ.

8. An event-driven communication device for a multi-threshold quantization system, the event-driven communication device for the multi-threshold quantization system is used to implement the event-driven communication method of the multi-threshold quantization system according to any one of claims 1-7, characterized in that, The device includes: An acquisition module for obtaining the input vector of the FIR system; A measurement module for obtaining the measurement vector through the measurement of a multi-threshold quantizer with m thresholds after obtaining the output vector through the FIR system according to the input vector; An estimation module for dynamically adjusting the trigger reference value of the event trigger through the data frequency of the measurement vector that has been sent independently by both the transmitter and the receiver. Obtain the trigger status value through the comparison result between the measurement vector and the reference value. After multiplying the trigger status value by the measurement vector, generate the transmission value. Among them, the transmitter of both the transmitter and the receiver is a multi-threshold quantizer, and the receiver is a remote estimation center. Transmit the transmission value to the remote estimation center through the communication network. The remote estimation center estimates the unknown parameters of the FIR system according to the transmission value. Among them, the event trigger is represented by Formula 1, and the Formula 1 is: Among them, represents the statistics up to the k-th moment, ψ τ is the system input value in the input vector, s k is the value in the measurement vector, and each system input ψ τ corresponds to s k outputs the s k value with the highest occurrence frequency, π k is the input vector, k is the statistical cut-off moment, l is the number of permutation cases where π k appears in the input sequence, l ≤ r n , r is the quantization order of the quantizer, and the initial value γ1 = 1.

9. An event-driven communication device of a multi-threshold quantization system, characterized in that, The event-driven communication device of the multi-threshold quantization system includes: A processor; A memory, on which computer-readable instructions are stored. When the computer-readable instructions are executed by the processor, the method described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that, Program code is stored in the computer-readable storage medium, and the program code can be called by the processor to execute the method described in any one of claims 1 to 7.

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