University of Hertfordshire

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Generating n-Scroll Chaotic Attractors From A Memristor-based Magnetized Hopfield Neural Network

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Original languageEnglish
JournalIEEE Transactions on Circuits and Systems II: Express Briefs
Early online date6 Oct 2022
DOIs
Publication statusE-pub ahead of print - 6 Oct 2022

Abstract

This brief presents a novel method to generate n-scroll
chaotic attractors. First, a magnetized Hopfield neural network
(HNN) with three neurons is modeled by introducing an improved
multi-piecewise memristor to describe the effect of electromagnetic
induction. Theoretical analysis and numerical simulation show that
the memristor-based magnetized HNN can generate multi-scroll
chaotic attractors with arbitrary number of scrolls. The number of
scrolls can be easily changed by adjusting the memristor control
parameters. Besides, complex initial offset boosting behavior is
revealed from the magnetized HNN. Finally, a magnetized HNN
circuit is designed and various typical attractors are verified.

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