{"title":"Synchronous control of memristive hindmarsh-rose neuron models with extreme multistability","authors":"Shaohui Yan, Jialong Wang, Jincai Song","doi":"10.1016/j.vlsi.2024.102280","DOIUrl":null,"url":null,"abstract":"<div><p>In this paper, the circuit simulation is achieved by the established Hindmarsh-Rose (HR) neuron model and the system is applied in projection synchronization. The chaotic behaviors of the neural network model are analyzed using bifurcation diagrams, Lyapunov exponents spectra, phase diagrams and time series diagrams. The dynamics analysis of the neuron model shows a variety of firing behaviors and extreme multistability behavior. The model is then simulated through circuit multisim to demonstrate the possibility in a physical sense. Finally, synchronization is induced to the memristive neural system through projection control, and the experimental results show that the model embodies a good synchronization effect in the process of projection synchronization, which helps to improve the security of signal transmission and the confidentiality of the system, and lays the foundation for the secure communication afterwards.</p></div>","PeriodicalId":54973,"journal":{"name":"Integration-The Vlsi Journal","volume":"100 ","pages":"Article 102280"},"PeriodicalIF":2.2000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Integration-The Vlsi Journal","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167926024001445","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, the circuit simulation is achieved by the established Hindmarsh-Rose (HR) neuron model and the system is applied in projection synchronization. The chaotic behaviors of the neural network model are analyzed using bifurcation diagrams, Lyapunov exponents spectra, phase diagrams and time series diagrams. The dynamics analysis of the neuron model shows a variety of firing behaviors and extreme multistability behavior. The model is then simulated through circuit multisim to demonstrate the possibility in a physical sense. Finally, synchronization is induced to the memristive neural system through projection control, and the experimental results show that the model embodies a good synchronization effect in the process of projection synchronization, which helps to improve the security of signal transmission and the confidentiality of the system, and lays the foundation for the secure communication afterwards.
期刊介绍：
Integration''s aim is to cover every aspect of the VLSI area, with an emphasis on cross-fertilization between various fields of science, and the design, verification, test and applications of integrated circuits and systems, as well as closely related topics in process and device technologies. Individual issues will feature peer-reviewed tutorials and articles as well as reviews of recent publications. The intended coverage of the journal can be assessed by examining the following (non-exclusive) list of topics:
Specification methods and languages; Analog/Digital Integrated Circuits and Systems; VLSI architectures; Algorithms, methods and tools for modeling, simulation, synthesis and verification of integrated circuits and systems of any complexity; Embedded systems; High-level synthesis for VLSI systems; Logic synthesis and finite automata; Testing, design-for-test and test generation algorithms; Physical design; Formal verification; Algorithms implemented in VLSI systems; Systems engineering; Heterogeneous systems.
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