Dynamic Analysis of a Physical SBT Memristor-Based Chaotic Circuit

Guo, Mei; Xue, Youbao; Gao, Zhenhao; Zhang, Yuman; Dou, Gang; Li, Yuxia

doi:10.1142/s0218127417300476

Cited by 29 publications

(15 citation statements)

References 17 publications

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“…Where P •V is the principal value of Cauchy in Hilbert transform. Hilbert transform is obtained in MATLAB by the algorithm given [28]. After truncating initial transient part, the instantaneous phase of x (t) and y (t) signals are exhibited in Figs.17 (a)-(b).…”

Section: Instantaneous Phasementioning

confidence: 99%

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Memristor-based Chaotic System with Upper-Lower Chaotic Attractors and Abundant Dynamical Behaviors

Yan

Ji’e

Wang

et al. 2021

Preprint

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Memristor, a controllable nonlinear element, is able to produce the chaotic signal easily. Most of the current researchers concentrate on the nonlinear properties of memristor, whereas its ability to control and adjust chaotic systems is often neglected. Thus a memristor-based chaotic system is designed to generate double-scroll chaotic attractors in this paper. The key features of the system are as follows: (a) when the polarity of the strength of memristor is adjusted, the upper-lower double-scroll chaotic attractors will be presented in the system. Chaotic motion of the system will be weakened and suppressed by properly selecting the strength of memristor, which enables the system to generate chaotic signals or suppress chaotic interference; (b) The system has very abundant dynamical behaviors, including sustained chaos, bistability, coexisting attractors, transient chaos, transient period and intermittency. To further explain the complex dynamics of the system, several basic dynamical behaviors, such as dissipation, symmetry, the stability of the equilibria, Poincare-maps, offset boosting control, recurrence analysis, 0-1 test analysis, and instantaneous phase analysis are displayed, either analytically or numerically. Moreover, the analogy circuit of the system is constructed. Experiment results prove that the PSPICE simulation and numerical analysis are consistent, which verifies the chaotic system's capability that produces chaos. Additionally, the proposed chaotic system has a strong immunity to any Gaussian noise with the zero mean. Therefore, a convenient method is employed to detect a weak multi-frequency signal embedded in the Gaussian noise based on the proposed chaotic system and the recursive back-stepping controller. The method based on the memristor-based chaos system provides a new train of thought for detecting weak signals, which is of great significance to promote the application of memristor.

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Section: Instantaneous Phasementioning

confidence: 99%

“…After that, memristor has attracted researchers more attention all over the world. The memristor is expected to have a wide range of applications thanks to its memory properties, such as information storage [3], neural networks [4], and brain-like computers [5].…”

Section: Introductionmentioning

confidence: 99%

Memristor-based Chaotic System with Upper-Lower Chaotic Attractors and Abundant Dynamical Behaviors

Yan

Ji’e

Wang

et al. 2021

Preprint

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“…As a nonlinear device, memristors are introduced to design chaotic circuits [11][12][13]. Some memristor-based nonlinear oscillators were created by replacing Chua's diodes with memristors, and the dynamical behaviors of these systems were analyzed and explored [14].…”

Section: Introductionmentioning

confidence: 99%

Complex Dynamics of a Novel Chaotic System Based on an Active Memristor

Song

Chang

2020

Electronics

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On the basis of the bistable bi-local active memristor (BBAM), an active memristor (AM) and its emulator were designed, and the characteristic fingerprints of the memristor were found under the applied periodic voltage. A memristor-based chaotic circuit was constructed, whose corresponding dynamics system was described by the 4-D autonomous differential equations. Complex dynamics behaviors, including chaos, transient chaos, heterogeneous coexisting attractors, and state-switches of the system were analyzed and explored by using Lyapunov exponents, bifurcation diagrams, phase diagrams, and Poincaré mapping, among others. In particular, a novel exotic chaotic attractor of the system was observed, as well as the singular state-switching between point attractors and chaotic attractors. The results of the theoretical analysis were verified by both circuit experiments and digital signal processing (DSP) technology.

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“…There have been many papers about the memristor [ 5 , 6 , 7 , 8 , 9 ]. In [ 6 ], a novel complex Lorenz system with a flux-controlled memristor is introduced and investigated.…”

Section: Introductionmentioning

confidence: 99%

Complex Dynamics in a Memcapacitor-Based Circuit

Yuan

Wang

et al. 2019

Entropy

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In this paper, a new memcapacitor model and its corresponding circuit emulator are proposed, based on which, a chaotic oscillator is designed and the system dynamic characteristics are investigated, both analytically and experimentally. Extreme multistability and coexisting attractors are observed in this complex system. The basins of attraction, multistability, bifurcations, Lyapunov exponents, and initial-condition-triggered similar bifurcation are analyzed. Finally, the memcapacitor-based chaotic oscillator is realized via circuit implementation with experimental results presented.

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Dynamic Analysis of a Physical SBT Memristor-Based Chaotic Circuit

Cited by 29 publications

References 17 publications

Memristor-based Chaotic System with Upper-Lower Chaotic Attractors and Abundant Dynamical Behaviors

Memristor-based Chaotic System with Upper-Lower Chaotic Attractors and Abundant Dynamical Behaviors

Complex Dynamics of a Novel Chaotic System Based on an Active Memristor

Complex Dynamics in a Memcapacitor-Based Circuit

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