Hyperchaotic circuit based on multi-coexistence phenomenon

By introducing memristors and gray wolf optimization algorithms into superchaotic circuits, optimizing system parameters and enhancing anti-interference capabilities, the problem of poor anti-interference capabilities and robustness of existing superchaotic circuits in complex electromagnetic environments is solved, and higher stability and safety are achieved.

CN119720895AActive Publication Date: 2025-03-28SHIJIAZHUANG UNIVERSITY
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Patent Information

Application Number
CN202510200505.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-02-24
Publication Date
2025-03-28
Estimated Expiration
2045-02-24

AI Technical Summary

Technical Problem

The existing superchaotic circuits have poor anti-interference ability and robustness in complex electromagnetic environments, and their stability is greatly affected by fluctuations in component parameters.

Method used

A superchaotic circuit based on multi-coexistence phenomena was designed. A four-dimensional superchaotic system model was constructed by introducing memristors, and Monte Carlo simulation was used to analyze the impact of component parameter fluctuations on the Lyapunov index to define the optimization range of system parameters. At the same time, the gray wolf optimization algorithm is used to optimize system parameters to enhance anti-interference ability and adaptability.

Benefits of technology

It significantly improves the complexity and security of the chaotic system, improves the stability and anti-interference ability of the system, and enables it to operate stably in complex electromagnetic environments.

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Abstract

The invention relates to a hyperchaotic circuit based on a multi-coexistence phenomenon, belongs to the field of nonlinear dynamics technology and digital circuits, and remarkably improves the complexity and unpredictability of a system by constructing a four-dimensional hyperchaotic system model containing a single linear term and introducing a memristor as a nonlinear feedback element. According to the method, the decoding resistance of the system is enhanced, the influence of element parameter fluctuation on the Lyapunov index is analyzed through Monte Carlo simulation, and the optimization range of system parameters is defined. The grey wolf optimization algorithm adopted by the invention can effectively optimize system parameters, and ensures that stable optimal parameters are obtained within a component tolerance range. The optimization method not only improves the stability of the system, but also enhances the anti-interference capability of the system. The technical scheme has a wide application prospect in the fields of secret communication, information security and the like, and attack means such as a chaos prediction technology and phase-space reconstruction can be effectively overcome.
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