An optimization device for a hyperchaotic circuit system

Abstract

The present invention relates to an optimization device for a hyperchaotic circuit system, belonging to the fields of nonlinear dynamics technology and digital circuits. By constructing a four-dimensional hyperchaotic system model with a single linear term and introducing a memristor as a nonlinear feedback element, the present invention significantly improves the complexity and unpredictability of the system. The present invention not only enhances the anti-cracking ability of the system, but also analyzes the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation, and defines the optimization range of system parameters. The grey wolf optimization algorithm adopted by the present invention can effectively optimize system parameters to ensure stable optimal parameters within the component tolerance range. The optimization device not only improves the stability of the system, but also enhances the anti-interference ability of the system. This technical solution has broad application prospects in the fields of secure communication and information security, and can effectively overcome attack means such as chaotic prediction technology and phase space reconstruction.

Description

Technical Field

[0001] The present invention relates to the fields of nonlinear dynamics technology and digital circuits, and particularly to an optimization device for a hyperchaotic circuit system. Background Art

[0002] Hyperchaotic circuits are an extension of chaos theory in high-dimensional systems, and their research background stems from the in-depth exploration of the behavior of complex dynamic systems. Since the discovery of the first classical three-dimensional chaotic system by Lorenz in the 1960s, chaos theory has been a hot topic in nonlinear science research. However, three-dimensional chaotic systems usually have only one positive Lyapunov exponent, and their dynamic behavior is relatively simple and easy to crack, which limits their application in fields such as encryption. To overcome this limitation, researchers have begun to explore hyperchaotic systems, which have two or more positive Lyapunov exponents and more complex and unpredictable dynamic behaviors. Hyperchaotic systems usually occur in four-dimensional and higher-dimensional nonlinear autonomous systems, and their dimensions are fractional dimensions above three. This complexity makes hyperchaotic systems have broad application prospects in fields such as secure communication, information security, and optimization algorithms. In recent years, with the development of electronic technology and nonlinear dynamics theory, the research on hyperchaotic circuits has gradually moved from theory to practical applications, and the introduction of new components such as memristors has further enriched the dynamic characteristics of hyperchaotic systems.

[0003] Although significant progress has been made in the theory and application of hyperchaotic circuits, there are still some development limitations. First, the complexity of hyperchaotic systems increases the difficulty of circuit design and implementation. The stability analysis and parameter optimization of high-dimensional systems become more complex and require more advanced numerical simulation and optimization algorithms. Second, the practical application of hyperchaotic circuits is limited by component performance and manufacturing processes. Chaotic circuits implemented with discrete components have problems such as large volume, high power consumption, and narrow frequency spectrum. Although the application of integrated circuit technology has solved these problems to a certain extent, the high-frequency performance and low-power design of high-dimensional hyperchaotic systems still face challenges. In addition, the practical application of hyperchaotic systems also needs to solve the problems of anti-interference ability and robustness. In a complex electromagnetic environment, the anti-interference ability of the circuit system directly affects its performance and reliability. Therefore, future research needs to make breakthroughs in improving the complexity, stability, anti-interference ability, and low-power design of hyperchaotic circuit systems to promote their wide application in more fields. Summary of the Invention

[0004] Based on this, it is necessary to provide an optimization device for a hyperchaotic circuit system in view of the problems that the stability of existing hyperchaotic circuits is greatly affected by factors such as component parameter fluctuations, and the anti-interference ability and robustness are poor in a complex electromagnetic environment.

[0005] The present invention is achieved through the following technical solutions: An optimization device for a hyperchaotic circuit system, comprising:

[0006] An input module, which is used to receive the initial system parameters of hyperchaotic dynamics and the initial range of component tolerances input by the user.

[0007] A hyperchaotic digital circuit modeling module, including a non-linear dynamics unit and a component parameter tolerance calculation unit. The non-linear dynamics unit constructs a four-dimensional hyperchaotic system model with a single linear term based on the principle of conditional symmetry, introduces a memristor as a non-linear feedback element, and is used to generate a hyperchaotic system equation to determine adjustable parameters. The component parameter tolerance calculation unit is used to analyze the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation and define the optimization range of system parameters.

[0008] A performance index calculation module, which includes a Lyapunov exponent calculation unit and an anti-interference strength calculation unit. The Lyapunov exponent calculation unit is used to solve the state differential equation of the hyperchaotic circuit system based on the hyperchaotic digital simulation circuit through numerical partial derivatives and calculate the Lyapunov exponent through the generated Jacobian matrix. The anti-interference strength calculation unit is used to calculate the anti-interference strength index according to the Lyapunov exponents output by the Lyapunov exponent calculation unit in two cases of denoising and non-denoising of the hyperchaotic digital simulation circuit.

[0009] A system parameter optimization module, including a grey wolf optimization algorithm unit and a hyperchaotic characteristic verification unit. The grey wolf optimization algorithm unit is used to generate an initial population according to the initial system parameters sent by the input module, calculate the fitness value of the system parameter population through the performance index provided by the performance index calculation module, and search for convergent system parameters based on the search mechanism of the grey wolf optimization algorithm. The hyperchaotic characteristic verification unit is used to verify the hyperchaotic characteristics of the converged parameters according to the initial range of component tolerances sent by the input module. If the hyperchaotic conditions are not met, the parameter is returned to the grey wolf optimization algorithm unit for re-optimization.

[0010] An output module, which is used to output the optimal system parameters that meet the hyperchaotic characteristics and are stable within the component tolerance range.

[0011] In one of the inventions, in the input module, the initial system parameters of hyperchaotic dynamics , denoted as , where represents the initial value of the i-th system parameter. The initial range of component tolerances , denoted as , where represents the initial tolerance range of the j-th component. The input of the input module also includes the population size N and the maximum number of iterations E of the grey wolf optimization algorithm.

[0012] In one of the inventions, in the hyperchaotic digital circuit modeling module, the system parameters a, b, c, d, and e are determined through the hyperchaotic system equations, and the four-dimensional hyperchaotic system model is described by the following differential equations:

[0013]

[0014] In the formula, , , , respectively represent the derivatives of the independent voltage sources of each path of the four-dimensional hyperchaotic circuit with respect to time t. a, b, c, d, and e respectively represent the linear coupling strength, nonlinear feedback term strength, damping coefficient, feedback gain of the fourth dimension, and nonlinear cross-term of the hyperchaotic dynamic system.

[0015] In one of the inventions, in the hyperchaotic digital circuit modeling module, the method for defining the parameter optimization range by analyzing the fluctuations of component parameters through Monte Carlo simulation is as follows:

[0016] Based on the four-dimensional hyperchaotic system model, set the fluctuation range of the system parameters according to the preset distribution.

[0017] Generate a preset number of system parameter samples through the Monte Carlo simulation method, calculate the Lyapunov exponents corresponding to the system parameter samples one by one, and statistically calculate the distribution characteristics of the results.

[0018] Observe the variation law of the Lyapunov exponent distribution with the fluctuations of the system parameters, and determine the threshold value when the Lyapunov exponent is stable by constraining the system parameter fluctuation interval.

[0019] In one of the inventions, in the performance index calculation module, the calculation method of the Lyapunov exponent is as follows:

[0020] Based on the hyperchaotic digital simulation circuit, solve the state differential equation of the hyperchaotic circuit system through numerical partial derivatives.

[0021] Among them, the state differential equation of the hyperchaotic circuit system is as follows:

[0022]

[0023] In the formula, x represents the independent voltage source of any path in the four-dimensional hyperchaotic circuit.

[0024] Take the partial derivative of the state differential equation of the hyperchaotic circuit system to construct the Jacobian matrix .

[0025] Among them, the expression of the Jacobian matrix is as follows:

[0026]

[0027]

[0028] Wherein, represents the element in the i-th row and j-th column of the Jacobian matrix.

[0029] For the Jacobian matrix , , ……, perform QR decomposition orthogonalization.

[0030] Calculate the Lyapunov exponent according to the orthogonal basis vectors after QR decomposition of the Jacobian matrix.

[0031] Wherein, the Lyapunov exponent has the following calculation formula:

[0032]

[0033] Wherein, represents the orthogonal basis vector after QR decomposition of the Jacobian matrix.

[0034] In one of the inventions, in the performance index calculation module, noise S is added to the noise data collected by the hyperchaotic digital simulation circuit, and the Lyapunov exponents output by the Lyapunov exponent calculation unit in two cases of denoising and non-denoising of the hyperchaotic digital simulation circuit are calculated respectively. The anti-interference strength index has the following calculation formula:

[0035]

[0036]

[0037]

[0038]

[0039] Wherein, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit in the case of denoising, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit in the case of non-denoising. , respectively represent the signal power and noise power of the four-dimensional hyperchaotic circuit.

[0040] In one of the inventions, in the system parameter optimization module, the steps of parameter optimization by the grey wolf optimization algorithm unit according to the initial system parameters sent by the input module are as follows:

[0041] Construct a gray wolf population G according to the initial system parameters, where each gray wolf represents a set of hyperchaotic circuit system parameters.

[0042] Construct a fitness function F according to the Lyapunov exponent and the anti-interference strength index M.

[0043] According to the hierarchical system and search mechanism of gray wolf individuals, update the positions of individuals in the gray wolf population until the maximum number of iterations, and calculate the optimal hyperchaotic circuit system parameters through the positions of the optimal, sub-optimal, and third-optimal gray wolves.

[0044] Verify the hyperchaotic characteristics of the optimal hyperchaotic circuit system parameters according to the initial tolerance range of components sent by the input module.

[0045] If the hyperchaotic conditions are not met, return the system parameters to the gray wolf optimization algorithm unit for re-optimization.

[0046] In one of the inventions, the calculation formula of the fitness function F is as follows:

[0047]

[0048]

[0049] In the formula, represents the i-th set of hyperchaotic circuit system parameters, , are weight coefficients.

[0050] In one of the inventions, the individual update formula in the gray wolf population is as follows:

[0051]

[0052]

[0053]

[0054] In the formula, , , represent the positions of the optimal, sub-optimal, and third-optimal gray wolves respectively, , represent the positions of the wolf pack individuals in the i-th round and the (i + 1)-th round respectively, , represent random parameter vectors respectively.

[0055] In one of the inventions, in the hyperchaotic characteristic verification unit, the hyperchaotic condition is: the hyperchaotic circuit system has at least one positive Lyapunov exponent.

[0056] Compared with the prior art, the present invention has the following beneficial effects:

[0057] The present invention proposes an optimization device for a hyperchaotic circuit system. By constructing a hyperchaotic circuit based on multi-coexistence phenomena, the present invention significantly enhances the complexity and security of the chaotic system. By introducing a memristor as a non-linear feedback element, a four-dimensional hyperchaotic system model with a single linear term is constructed, enabling the hyperchaotic circuit system to have more complex dynamic behaviors and higher unpredictability. The unique memory function and nano-scale size structure of the memristor not only enhance the multi-stable characteristics of the hyperchaotic circuit system but also reduce the size and energy consumption of the hyperchaotic circuit system. The complexity and unpredictability of the four-dimensional hyperchaotic circuit system in the present invention have important application values in fields such as secure communication and information encryption, and can effectively improve the security of the hyperchaotic circuit system. In addition, the present invention analyzes the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation, defines the optimization range of the parameters of the hyperchaotic circuit system, and further enhances the stability and reliability of the hyperchaotic circuit system.

[0058] The present invention also significantly enhances the anti-interference ability and adaptability of the hyperchaotic circuit system. By calculating the anti-interference strength index and evaluating the performance differences of the hyperchaotic digital simulation circuit with and without denoising, the parameters of the hyperchaotic circuit system are optimized, thereby enhancing the anti-interference ability of the hyperchaotic circuit system. The improvement of the anti-interference ability of the present invention is particularly important for applications in complex electromagnetic environments, and can ensure the stable operation of the hyperchaotic circuit system under noise interference. In addition, the present invention uses the grey wolf optimization algorithm to optimize the parameters of the hyperchaotic circuit system to ensure stable optimal system parameters within the component tolerance range. This optimization method not only improves the stability of the hyperchaotic circuit system but also enhances the adaptability of the hyperchaotic circuit system, enabling it to maintain high performance under different working conditions. Description of the Drawings

[0059] Figure 1 It is a schematic structural diagram of an optimization device for a hyperchaotic circuit system in this embodiment;

[0060] Figure 2 It is a step diagram of parameter optimization by the grey wolf optimization algorithm unit in this embodiment. Detailed Embodiments

[0061] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0062] It should be noted that when a component is referred to as "installed on" another component, it can be directly on the other component or there can be an intermediate component. When a component is considered to be "set on" another component, it can be directly set on the other component or there may be an intermediate component at the same time. When a component is considered to be "fixed to" another component, it can be directly fixed to the other component or there may be an intermediate component at the same time.

[0063] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this invention belongs. The terms used in the description of the present invention herein are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "or / and" used herein includes any and all combinations of one or more of the related listed items.

[0064] Figure 1 It is a schematic structural diagram of an optimization device for a hyperchaotic circuit system in this embodiment. Figure 2 It is a step diagram for the parameter optimization of the grey wolf optimization algorithm unit in this embodiment. Please refer to Figure 1 - Figure 2 , this embodiment provides an optimization device for a hyperchaotic circuit system, including:

[0065] An input module, which is used to receive the initial system parameters of the hyperchaotic dynamics and the initial range of component tolerances input by the user. In this embodiment, the initial system parameters of the hyperchaotic dynamics of the input module , denoted as , where represents the initial value of the i-th system parameter. The initial range of component tolerances , denoted as , where represents the initial tolerance range of the j-th component. The input of the input module also includes the population size N and the maximum number of iterations E of the grey wolf optimization algorithm. The population size selected in this embodiment is 20, and the maximum number of iterations is 50.

[0066] A hyperchaotic digital circuit modeling module, including a non-linear dynamics unit and a component parameter tolerance calculation unit. The non-linear dynamics unit constructs a four-dimensional hyperchaotic system model with a single linear term based on the principle of conditional symmetry, introduces a memristor as a non-linear feedback element, and is used to generate the hyperchaotic system equation to determine the adjustable parameters. The component parameter tolerance calculation unit is used to analyze the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation and define the optimization range of system parameters.

[0067] In the hyperchaotic digital circuit modeling module, the system parameters a, b, c, d, e are determined through the hyperchaotic system equation, and the four-dimensional hyperchaotic system model is described by the following differential equation:

[0068]

[0069] wherein , , , respectively represent the derivatives with respect to time t of the independent voltage sources of each path of the four-dimensional hyperchaotic circuit, and a, b, c, d, and e respectively represent the linear coupling strength, the strength of the non-linear feedback term, the damping coefficient, the feedback gain of the fourth dimension, and the non-linear cross term of the hyperchaotic dynamical system.

[0070] In the hyperchaotic digital circuit modeling module, the method for defining the parameter optimization range by analyzing the fluctuations of component parameters through Monte Carlo simulation is as follows:

[0071] Based on the four-dimensional hyperchaotic system model, set the fluctuation range of the system parameters according to a preset distribution. In this embodiment, the fluctuation range of the system parameters is set according to the normal distribution.

[0072] Generate a preset number of system parameter samples through the Monte Carlo simulation method, calculate the Lyapunov exponents corresponding to the system parameter samples one by one, and statistically analyze the distribution characteristics of the calculation results. In this embodiment, the number of system parameter samples is 1000.

[0073] Observe the variation law of the Lyapunov exponent distribution with the fluctuation of the system parameters, and determine the threshold value when the Lyapunov exponent is stable by constraining the fluctuation range of the system parameters.

[0074] Performance index calculation module, the performance index calculation module includes a Lyapunov exponent calculation unit and an anti-interference strength calculation unit. The Lyapunov exponent calculation unit is used to solve the state differential equation of the hyperchaotic circuit system through numerical partial derivatives based on the hyperchaotic digital simulation circuit, and calculate the Lyapunov exponent through the generated Jacobian matrix. The anti-interference strength calculation unit is used to calculate the anti-interference strength index according to the Lyapunov exponents output by the Lyapunov exponent calculation unit in two cases of denoising and non-denoising of the hyperchaotic digital simulation circuit.

[0075] In the performance index calculation module, the calculation method of the Lyapunov exponent is as follows:

[0076] Solve the state differential equation of the hyperchaotic circuit system through numerical partial derivatives based on the hyperchaotic digital simulation circuit.

[0077] Among them, the state differential equation of the hyperchaotic circuit system is as follows:

[0078]

[0079] wherein, x represents the independent voltage source of any path in the four-dimensional hyperchaotic circuit.

[0080] Take the partial derivative of the state differential equation of the hyperchaotic circuit system to construct the Jacobian matrix .

[0081] Among them, the Jacobian matrix has the following expression:

[0082]

[0083]

[0084] In the formula, represents the element in the i-th row and j-th column of the Jacobian matrix.

[0085] Perform QR decomposition orthogonalization on the Jacobian matrix , , ……, .

[0086] Calculate the Lyapunov exponent according to the orthogonal basis vectors after QR decomposition of the Jacobian matrix.

[0087] Among them, the calculation formula of the Lyapunov exponent is as follows:

[0088]

[0089] In the formula, represents the orthogonal basis vector after QR decomposition of the Jacobian matrix.

[0090] In the performance index calculation module, add noise S to the noise data collected by the hyperchaotic digital simulation circuit, and calculate the Lyapunov exponents output by the Lyapunov exponent calculation unit in the hyperchaotic digital simulation circuit with and without noise reduction respectively. The anti-interference strength index has the following calculation formula:

[0091]

[0092]

[0093]

[0094]

[0095] In the formula, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit in the case of noise reduction, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit in the case of not reducing noise. , respectively represent the signal power and noise power of the four-dimensional hyperchaotic circuit.

[0096] The system parameter optimization module includes a gray wolf optimization algorithm unit and a hyperchaotic characteristic verification unit. The gray wolf optimization algorithm unit is used to generate an initial population according to the initial system parameters sent by the input module, calculate the fitness value of the system parameter population through the performance index provided by the performance index calculation module, and search for the convergent system parameters based on the search mechanism of the gray wolf optimization algorithm. The hyperchaotic characteristic verification unit is used to verify the hyperchaotic characteristics of the converged parameters according to the initial range of component tolerances sent by the input module. If the hyperchaotic conditions are not met, the parameter is returned to the gray wolf optimization algorithm unit for re-optimization.

[0097] In the system parameter optimization module, the steps for the gray wolf optimization algorithm unit to perform parameter optimization according to the initial system parameters sent by the input module are as follows:

[0098] Construct a gray wolf population G according to the initial system parameters, and each gray wolf represents a set of hyperchaotic circuit system parameters.

[0099] Construct a fitness function F according to the Lyapunov exponent and the anti-interference strength index M.

[0100] According to the hierarchical system and search mechanism of gray wolf individuals, update the positions of individuals in the gray wolf population until the maximum number of iterations, and calculate the best hyperchaotic circuit system parameters through the positions of the optimal, sub-optimal, and third-optimal gray wolves.

[0101] Verify the hyperchaotic characteristics of the best hyperchaotic circuit system parameters according to the initial range of component tolerances sent by the input module.

[0102] If the hyperchaotic conditions are not met, return the system parameter to the gray wolf optimization algorithm unit for re-optimization.

[0103] Among them, the calculation formula of the fitness function F is as follows:

[0104]

[0105]

[0106] In the formula, represents the i-th set of hyperchaotic circuit system parameters, , are weight coefficients.

[0107] In one embodiment, the individual update formula in the gray wolf population is as follows:

[0108]

[0109]

[0110]

[0111] In the formula, , , represent the positions of the optimal, sub-optimal, and third-optimal grey wolves respectively, , represent the positions of the individuals in the i-th and (i + 1)-th rounds of the wolf pack respectively, , represent the random parameter vectors respectively.

[0112] In the hyperchaotic characteristic verification unit, the hyperchaotic condition is that the hyperchaotic circuit system has at least one positive Lyapunov exponent.

[0113] The output module is used to output the optimal system parameters that satisfy the stability of the hyperchaotic characteristics within the component tolerance range.

[0114] An optimization device for a hyperchaotic circuit system in this embodiment significantly improves the complexity and security of the chaotic system by constructing a hyperchaotic circuit based on the multi-coexistence phenomenon. By introducing a memristor as a non-linear feedback element, a four-dimensional hyperchaotic system model with a single linear term is constructed, enabling the system to have more complex dynamic behaviors and higher unpredictability. The complexity and unpredictability of the four-dimensional hyperchaotic circuit system in this embodiment have important application values in fields such as secure communication and information encryption, and can effectively improve the security of the system. In addition, in this embodiment, the Monte Carlo simulation is used to analyze the influence of component parameter fluctuations on the Lyapunov exponent, and the optimization range of the system parameters is defined, further enhancing the stability and reliability of the system. This embodiment has also achieved remarkable results in improving the anti-interference ability and stability of the hyperchaotic circuit. By analyzing the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation, the optimization range of the system parameters is defined, thereby ensuring the stable operation of the system within the component tolerance range. In addition, this embodiment also calculates the anti-interference strength index to evaluate the performance difference of the hyperchaotic digital simulation circuit in the cases of denoising and non-denoising, further optimizing the system parameters and enhancing the anti-interference ability of the system. For example, the ultra-wideband chaotic signal has advantages such as large bandwidth, low latency, high quality, and strong anti-interference ability, and can significantly improve the anti-interference performance of the system. This improvement in anti-interference ability is particularly important for applications in complex electromagnetic environments and can ensure the stable operation of the system under noise interference.

[0115] This embodiment also significantly enhances the anti-interference ability and adaptability of the hyperchaotic circuit. By calculating the anti-interference strength index, the performance differences of the hyperchaotic digital simulation circuit under denoising and non-denoising conditions are evaluated, so as to optimize the system parameters and enhance the anti-interference ability of the system. The improvement of the anti-interference ability in this embodiment is particularly important for applications in complex electromagnetic environments, ensuring that the system can still operate stably under noise interference. In addition, this embodiment uses the grey wolf optimization algorithm to optimize the system parameters to ensure stable optimal system parameters within the component tolerance range. This optimization method not only improves the stability of the system but also enhances the adaptability of the system, enabling it to maintain high performance under different working conditions. This embodiment significantly improves the complexity and security of the system by constructing a hyperchaotic circuit based on the multi-coexistence phenomenon. First, the hyperchaotic system has two or more positive Lyapunov exponents, and its dynamic behavior is more complex than that of traditional chaotic systems, which makes the system have higher anti-cracking performance in fields such as secure communication and information security. For example, hyperchaotic signals can effectively overcome attack means such as chaotic prediction technology and phase space reconstruction, thus enhancing the security of the system. In addition, by introducing memristors as non-linear feedback elements, this embodiment further enriches the dynamic characteristics of the system, enabling it to generate the coexistence phenomenon of multi-attractors or infinitely many attractors. This complexity and unpredictability not only improve the security of the system but also provide a broader space for the application of the system in encryption algorithms and communication fields.

[0116] The above embodiments only represent several implementation manners of this embodiment, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the embodiment patent. It should be noted that for those of ordinary skill in the art, without departing from the concept of this embodiment, several deformations and improvements can still be made, and these all belong to the protection scope of this embodiment. Therefore, the protection scope of this embodiment patent shall be subject to the appended claims.

Claims

1. An optimization device for a hyperchaotic circuit system, characterized in that, Including: An input module for receiving the initial system parameters of the hyperchaotic dynamics and the initial range of component tolerances input by the user; A hyperchaotic digital circuit modeling module, including a non-linear dynamics unit and a component parameter tolerance calculation unit; the non-linear dynamics unit constructs a four-dimensional hyperchaotic system model with a single linear term based on the principle of conditional symmetry, introduces a memristor as a non-linear feedback element, and is used to generate the hyperchaotic system equation to determine the adjustable parameters; the component parameter tolerance calculation unit is used to analyze the influence of component parameter fluctuations on the Lyapunov exponent through Monte Carlo simulation and define the system parameter optimization range; A performance index calculation module, the performance index calculation module includes a Lyapunov exponent calculation unit and an anti-interference strength calculation unit; the Lyapunov exponent calculation unit is used to solve the state differential equation of the hyperchaotic circuit system through numerical partial derivatives based on the hyperchaotic digital simulation circuit, and calculate the Lyapunov exponent through the generated Jacobian matrix; the anti-interference strength calculation unit is used to calculate the anti-interference strength index according to the Lyapunov exponents output by the Lyapunov exponent calculation unit in two cases of denoising and non-denoising of the hyperchaotic digital simulation circuit; A system parameter optimization module, including a grey wolf optimization algorithm unit and a hyperchaotic characteristic verification unit; the grey wolf optimization algorithm unit is used to generate an initial population according to the initial system parameters sent by the input module, calculate the fitness value of the system parameter population through the performance index provided by the performance index calculation module, and search for the convergent system parameters based on the search mechanism of the grey wolf optimization algorithm; the hyperchaotic characteristic verification unit is used to verify the hyperchaotic characteristics of the converged parameters according to the initial range of component tolerances sent by the input module. If the hyperchaotic conditions are not met, the parameters are returned to the grey wolf optimization algorithm unit for re-optimization; An output module for outputting the optimal system parameters that satisfy the hyperchaotic characteristics and are stable within the component tolerance range.

2. The optimization device of a hyperchaotic circuit system according to claim 1, characterized in that In the input module, the initial system parameters of the hyperchaotic dynamics , denoted as , where represents the initial value of the i-th system parameter; the initial range of component tolerances , denoted as , where represents the initial range of tolerances of the j-th component; the input of the input module further includes the population size N and the maximum number of iterations E of the grey wolf optimization algorithm.

3. The optimization device of a hyperchaotic circuit system according to claim 1, characterized in that, In the hyperchaotic digital circuit modeling module, the system parameters a, b, c, d, e are determined by the hyperchaotic system equation, and the four-dimensional hyperchaotic system model is described by the following differential equation: In the formula, , , , respectively represent the derivatives with respect to time t of the independent voltage sources of each path of the four-dimensional hyperchaotic circuit, and a, b, c, d, and e respectively represent the linear coupling strength, the strength of the non-linear feedback term, the damping coefficient, the feedback gain of the fourth dimension, and the non-linear cross term of the hyperchaotic dynamical system.

4. The optimization device of a hyperchaotic circuit system according to claim 1, characterized in that In the hyperchaotic digital circuit modeling module, the method for defining the parameter optimization range by analyzing the component parameter fluctuations through Monte Carlo simulation is as follows: Based on the four-dimensional hyperchaotic system model, set the fluctuation range of the system parameters according to a preset distribution; Generate a preset number of system parameter samples through the Monte Carlo simulation method, calculate the Lyapunov exponents corresponding to the system parameter samples one by one, and statistically analyze the distribution characteristics of the calculation results; Observe the variation law of the Lyapunov exponent distribution with the fluctuation of the system parameters, and determine the threshold value when the Lyapunov exponent is stable by constraining the system parameter fluctuation interval.

5. The optimization device of a hyperchaotic circuit system according to claim 1, characterized in that, In the performance index calculation module, the calculation method of the Lyapunov exponent is as follows: Solve the state differential equation of the hyperchaotic circuit system through numerical partial derivatives based on the hyperchaotic digital simulation circuit; Among them, the state differential equation of the hyperchaotic circuit system is as follows: Wherein, x represents an independent voltage source of any path in the four-dimensional hyperchaotic circuit; Take the partial derivative of the state differential equation of the hyperchaotic circuit system to construct the Jacobian matrix ; Among them, the Jacobian matrix has the following expression: In the formula, represents the element in the i-th row and j-th column of the Jacobian matrix; Perform QR decomposition orthogonalization on the Jacobian matrix , , ……, ; Calculate the Lyapunov exponent according to the orthogonal basis vectors after the QR decomposition of the Jacobian matrix; Among them, the Lyapunov exponent has the following calculation formula: In the formula, represents the orthogonal basis vectors after the QR decomposition of the Jacobian matrix.

6. The optimization device of a hyperchaotic circuit system according to claim 1, characterized in that In the performance index calculation module, noise S is added to the noise data collected by the hyperchaotic digital simulation circuit, and the Lyapunov exponents output by the Lyapunov exponent calculation unit in the hyperchaotic digital simulation circuit with and without denoising are calculated respectively; the anti-interference strength index The calculation formula is as follows: In the formula, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit under the condition of denoising, represents the Lyapunov exponent output by the Lyapunov exponent calculation unit without denoising; , respectively represent the signal power and noise power of the four-dimensional hyperchaotic circuit.

7. An optimization device for a hyperchaotic circuit system according to claim 1, characterized in that, In the system parameter optimization module, the steps of parameter optimization by the grey wolf optimization algorithm unit according to the initial system parameters sent by the input module are as follows: Construct a grey wolf population G according to the initial system parameters, and each grey wolf represents a set of the hyperchaotic circuit system parameters; Construct a fitness function F according to the Lyapunov exponent and the anti-interference strength index M; According to the hierarchical system and search mechanism of the grey wolf individuals, update the positions of the individuals in the grey wolf population until the maximum number of iterations, and calculate the best hyperchaotic circuit system parameters through the positions of the optimal, sub-optimal, and third-optimal grey wolves; Verify the hyperchaotic characteristics of the best hyperchaotic circuit system parameters according to the initial range of component tolerances sent by the input module; If the hyperchaotic condition is not satisfied, return the system parameters to the grey wolf optimization algorithm unit for re-optimization.

8. An optimization device for a hyperchaotic circuit system according to claim 7, characterized in that, The calculation formula of the fitness function F is as follows: In the formula, represents the parameters of the i-th group of the hyperchaotic circuit systems, , are weight coefficients.

9. The optimization device of a hyperchaotic circuit system according to claim 7, characterized in that, The formula for updating the individuals in the grey wolf population is as follows: In the formula, , , represent the positions of the optimal, sub-optimal, and third-optimal grey wolves respectively, , represent the positions of the individuals in the i-th and (i + 1)-th rounds of the wolf pack respectively, , represent random parameter vectors respectively.

10. The optimization device of a hyperchaotic circuit system according to claim 7, characterized in that, In the hyperchaotic characteristic verification unit, the hyperchaotic condition is that the hyperchaotic circuit system has at least one positive Lyapunov exponent.

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