Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

Chen, Mo; Ren, Xue; Wu, Huagan; Xu, Quan; Bao, Bocheng

doi:10.1631/fitee.1900360

Cited by 54 publications

(9 citation statements)

References 44 publications

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“…Based on the former analyses, the proposed system (1) has significant initial value sensitivity, which reveals complex extreme multi-stability phenomena. Additionally, in the process of investigating the system (1)'s extreme multi-stability, an intriguing phenomenonknown as initial offset-boosting behavior [36][37]…”

Section: Hidden Coexisting Attractorsmentioning

confidence: 99%

Generating novel multi-scroll chaotic attractors via fractal transformation

et al. 2022

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The fractal and chaos are bound tightly, and their relevant researches are well-established. Few of them, however, concentrates on the research of the possibility of combining the fractal and the chaotic systems to generate multi-scroll chaotic attractors. This paper presents a novel non-equilibrium point chaotic system, exhibiting extremely rich and complex hidden behaviors including chaos, hyper-chaos, multiscroll attractors, extreme multi-stability and initial offset-boosting. The proposed system is combined with fractal transformation respectively, and a new class of multi-scroll attractors, such as multi-ring attractors and separated-scroll attractors, is observed. Particularly, swallow-shaped attractors for the first time is found. Moreover, another efficient method to generate a different class of chaotic attractors uses parabola transformation and triangle transformation. Additionally, the spectrum entropy (SE) complexity is employed to discuss the complexity of the proposed system before and after fractal, resulting in a chaotic sequences with fractal transformation that has higher complexity. Finally, we develop a hardware platform to implement the presented attractors before and after fractal in a way to confirm the accuracy of the numerical simulations, providing a theoretical basis for the next application in image encryption.

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Section: Hidden Coexisting Attractorsmentioning

confidence: 99%

Generating novel multi-scroll chaotic attractors via fractal transformation

et al. 2022

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“…In addition, Ascoli et al constructed an extended bistable memristor with two coexisting pinched hysteresis loops under different initial states [15]. Meanwhile, many important achievements based on the mathematical memristors have been made constantly, especially the investigation of memristor-based multi-stable systems [16][17][18][19]. Although many memristive multi-stable systems have been developed by using existing memristors, the generation of their multi-stable behavior is stochastic and uncontrolled.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Stable Memristor and its Application in a Neural Network

Lin

Wang

Hong

et al. 2020

IEEE Trans. Circuits Syst. II

142

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Nowadays, there is a lot of study on memristorbased systems with multistability. However, there is no study on memristor with multistability. This brief constructs a mathematical memristor model with multistability. The origin of the multi-stable dynamics is revealed using standard nonlinear theory as well as circuit and system theory. Moreover, the multi-stable memristor is applied to simulate a synaptic connection in a Hopfield neural network. The memristive neural network successfully generates infinitely many coexisting chaotic attractors unobserved in previous Hopfield-type neural networks. The results are also confirmed in analog circuits based on commercially available electronic elements.

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“…Researchers pays great effort to learn how to get those attractors controlled by parameters (Li et al 2017b;Kingni et al 2020;Ma et al 2021;Zhang et al 2018;Mezatio et al 2019) or by initial conditions (Bao et al 2020;Chen et al 2020;Zhang et al 2020;Wu et al 2019a;Ding et al 2020). Even in those memristive systems (Chen et al 2019;Kengne et al 2018;Lu et al 2020;Wu et al 2019b;Yuan et al 2019) offset boosting is still a hot spot for discussion.…”

Section: Introductionmentioning

confidence: 99%

On Offset Boosting in Chaotic System

Jiang

2021

Chaos Theory and Applications

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Offset boosting is an important issue for chaos control due to its broadband property and polarity control. There are two main approaches to realize offset boosting. One is resort to parameter introducing where an offset booster realizes attractor boosting. The other one is by the means of periodic function or absolute value function where any self-reproduced or doubled attractors with diverse offset are extracted out by a specific initial condition. The former also provides a unique window for observing multistability and the latter gives the direction for constructing desired multistability.

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Periodically varied initial offset boosting behaviors in a memristive system with cosine memductance

Cited by 54 publications

References 44 publications

Generating novel multi-scroll chaotic attractors via fractal transformation

Generating novel multi-scroll chaotic attractors via fractal transformation

A Multi-Stable Memristor and its Application in a Neural Network

On Offset Boosting in Chaotic System

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