Chaos in a Simplest Cyclic Memristive Neural Network

DOI10.1142/S0218127422500420zbMath1494.34125OpenAlexW4220988152MaRDI QIDQ5064643

Paul Didier Kamdem Kuate, Shaobo He, Chunbiao Li, Qiang Lai, Cong Lai

Publication date: 16 March 2022

Published in: International Journal of Bifurcation and Chaos (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218127422500420

zbMATH Keywords

chaoscoexisting attractorsmicrocontrollermemristive neural networksimplest cyclic connection

Mathematics Subject Classification ID

Topological structure of integral curves, singular points, limit cycles of ordinary differential equations (34C05) Neural networks for/in biological studies, artificial life and related topics (92B20) Bifurcation theory for ordinary differential equations (34C23) Strange attractors, chaotic dynamics of systems with hyperbolic behavior (37D45) Qualitative investigation and simulation of ordinary differential equation models (34C60) Complex behavior and chaotic systems of ordinary differential equations (34C28) Circuits in qualitative investigation and simulation of models (94C60)

Related Items (3)

A mem-element Wien-Bridge circuit with amplitude modulation and three kinds of offset boosting ⋮ Chaos and multi-layer attractors in asymmetric neural networks coupled with discrete fractional memristor ⋮ \( \mu \)-stability and instability of multiple equilibrium points in delayed neural networks with general discontinuous activation functions

Cites Work

• Multiple attractors in a non-ideal active voltage-controlled memristor based Chua's circuit
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• 3-D CELLULAR NEURAL NETWORKS WITH CYCLIC CONNECTIONS CANNOT EXHIBIT CHAOS
• Coexisting Infinite Equilibria and Chaos
• Dynamics editing based on offset boosting
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• Neural networks and physical systems with emergent collective computational abilities.
• Neurons with graded response have collective computational properties like those of two-state neurons.
• A Unified Chaotic System with Various Coexisting Attractors

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