A new simple chaotic circuit based on memristor and meminductor

Liu, Xingce; Mou, Jun; Wang, Jieyang; Liu, Jian; Cao, Yinghong

doi:10.1140/epjp/s13360-021-02182-5

Cited by 13 publications

(5 citation statements)

References 47 publications

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“…Thus, the results proposed in this work are beneficial to those areas which the circuit elements with memory are involved, e.g. the analysis and designing of chaotic oscillators (Atan, 2020; Sun et al , 2020; Li et al , 2021; Liu et al , 2021), the chaotic system-based power management of networks of oscillators (Bucolo et al , 2021) and neuromorphic circuits and neural networks (Guo et al , 2020; Oshio et al , 2021; Sun et al , 2021; Xu et al , 2021).…”

Section: Discussionmentioning

confidence: 99%

Generic analytical models of memelement and inverse memelement with time-dependent memory effects

Banchuin

2023

COMPEL

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Purpose The purpose of this paper is to originally present the generic analytical models of memelement and inverse memelement with time-dependent memory effect. Design/methodology/approach The variable order forward Grünwald–Letnikov fractional derivative and the memristor and inverse memristor models proposed by Fouda et al. have been adopted as the basis. Both analytical and numerical studies have been conducted. The applications to the candidate practical memristor and inverse memelements have also been presented. Findings The generic analytical models of memelement and inverse memelement with time-dependent memory effect, the simplified ones for DC and AC signal-based analyses and the equations of crucial parameters have been derived. Besides the well-known opposite relationships with frequency, the Lissajous patterns of memelement and inverse memelement also use the opposite relationships with the time. The proposed models can be well applied to the practical elements. Originality/value To the best of the authors’ knowledge, for the first time, the models’ memelement and inverse memelement with time-dependent memory effect have been presented. A new contrast between these elements has been discovered. The resulting models are applicable to the practical elements.

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Section: Discussionmentioning

confidence: 99%

Generic analytical models of memelement and inverse memelement with time-dependent memory effects

Banchuin

2023

COMPEL

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“…Verification is provided in the form of circuit simulations. A very simple circuit which becomes chaotic is described in paper [148]. It consists of a series connection of memristor, meminductor and linear capacitor.…”

Section: Chaotic Oscillators With Memelementsmentioning

confidence: 99%

Chaos in Analog Electronic Circuits: Comprehensive Review, Solved Problems, Open Topics and Small Example

Petržela

2022

Mathematics

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This paper strives to achieve a comprehensive review of chaos in analog circuits and lumped electronic networks. Readers will be guided from the beginning of the investigations of simple electronic circuits to the current trends in the research into chaos. The author tries to provide the key references related to this issue, including papers describing modern numerical algorithms capable of localizing chaotic and hyperchaotic motion in complex mathematical models, interesting full on-chip implementations of chaotic systems, possible practical applications of entropic signals, fractional-order chaotic systems and chaotic oscillators with mem-elements.

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“…In recent years, as a new type of electronic component, the memristor has important application in the fields of neural networks [18][19][20][21][22], image encryption [22][23][24][25][26], synchronization [27][28][29][30][31] and nonlinear chaotic circuit systems [32][33][34]. The memristor is the fourth fundamental circuit component on the basis of the existing three types of basic electronic components (resistor, capacitor and inductor) [35].…”

Section: Introductionmentioning

confidence: 99%

Multiple firing patterns, energy conversion and hardware implementation within Hindmarsh-Rose-improved neuron model

Yan,

Jiang,

Zhang

et al. 2024

Phys. Scr.

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The transmission of information between neurons is accomplished in living organisms through synapses. The memristor is an electronic component that simulates the tunability of the strength of biological synaptic connections in artificial neural networks. This article constructs a novel type of locally active memristor and verifies by nonlinear theoretical analysis, locally active analysis and circuit simulation. The designed memristor is simulated as a biological autapse of Hindmarsh-Rose(HR) neuron to obtain the improved HR neuron model of memristive autapse, and the Hamilton energy is obtained according to Helmholtz theorem. By varying the external forcing current and the memristive autapse strength, this article analyses the changes of the Hamilton energy and explores its self-excited and hidden firing behavior. The analog circuit simulation and digital circuit implementation of the HR model confirm the consistency between the mathematical model and the actual behavior, which can advance the field of neuroscience and artificial intelligence.

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A new simple chaotic circuit based on memristor and meminductor

Cited by 13 publications

References 47 publications

Generic analytical models of memelement and inverse memelement with time-dependent memory effects

Generic analytical models of memelement and inverse memelement with time-dependent memory effects

Chaos in Analog Electronic Circuits: Comprehensive Review, Solved Problems, Open Topics and Small Example

Multiple firing patterns, energy conversion and hardware implementation within Hindmarsh-Rose-improved neuron model

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