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

Hairong  Lin; Chunhua Wang; Yichuang Sun; Ting  Wang

doi:10.1109/TCSII.2022.3212394

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

Hairong Lin, Chunhua Wang, Yichuang Sun, Ting Wang

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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.

Original language	English
Pages (from-to)	311 - 315
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	70
Issue number	1
Early online date	6 Oct 2022
DOIs	https://doi.org/10.1109/TCSII.2022.3212394
Publication status	E-pub ahead of print - 6 Oct 2022

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© 2023 IEEE. This is the accepted manuscript version of an article which has been published in final form at https://doi.org/10.1109/TCSII.2022.3212394
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title = "Generating n-Scroll Chaotic Attractors From A Memristor-based Magnetized Hopfield Neural Network",

abstract = "This brief presents a novel method to generate n-scrollchaotic attractors. First, a magnetized Hopfield neural network(HNN) with three neurons is modeled by introducing an improvedmulti-piecewise memristor to describe the effect of electromagneticinduction. Theoretical analysis and numerical simulation show thatthe memristor-based magnetized HNN can generate multi-scrollchaotic attractors with arbitrary number of scrolls. The number ofscrolls can be easily changed by adjusting the memristor controlparameters. Besides, complex initial offset boosting behavior isrevealed from the magnetized HNN. Finally, a magnetized HNNcircuit is designed and various typical attractors are verified.",

author = "Hairong Lin and Chunhua Wang and Yichuang Sun and Ting Wang",

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AU - Lin, Hairong

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AB - This brief presents a novel method to generate n-scrollchaotic attractors. First, a magnetized Hopfield neural network(HNN) with three neurons is modeled by introducing an improvedmulti-piecewise memristor to describe the effect of electromagneticinduction. Theoretical analysis and numerical simulation show thatthe memristor-based magnetized HNN can generate multi-scrollchaotic attractors with arbitrary number of scrolls. The number ofscrolls can be easily changed by adjusting the memristor controlparameters. Besides, complex initial offset boosting behavior isrevealed from the magnetized HNN. Finally, a magnetized HNNcircuit is designed and various typical attractors are verified.

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

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