Three-Dimensional Space Chaotic Scrolls Generated by Memristive Hopfield Neural Network And Its Application In Robot Path Planning

Abstract In this paper, a novel three-dimensional space-scroll chaotic attractor are constructed by introducing piece-wise linear memristors into a three-neurons-based Hopfield neural network to simulate the electromagnetic influence on neural dynamics. The dynamical behaviors of the novel memristive Hopfield neural network is discussed by means of numerical methods including the Lyapunov exponent spectrum, bifurcation diagram, phase plots and dynamic maps. Furthermore, we also investigated different neurons subject to the memristive electromagnetic influence, where the two-dimensional grid-scroll chaotic attractors can be generated by one neuron subjects to the electromagnetic influence and three-dimensional space-scroll chaotic attractors can be generated by all of the neurons subject to the memristive electromagnetic influence. Moreover, we present the three-dimensional space-scroll scroll attractor-based chaotic mobile robot system. Superiority of the proposed space-scroll-based chaotic mobile robot system compared to existing methods has been demonstrated through numerical simulations.

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Publication Details

Journal
Journal of Computational and Nonlinear Dynamics
Published
2024-09-30
DOI
https://doi.org/10.1115/1.4066729
Primary Topic
Neural Networks and Applications
Type
article
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article

Three-Dimensional Space Chaotic Scrolls Generated by Memristive Hopfield Neural Network And Its Application In Robot Path Planning

Mingjun Tang, Linyang Guo, Runxian Yang, Chunlin Xu et al.
Journal of Computational and Nonlinear Dynamics
Neural Networks and Applications
article

Three-Dimensional Space Chaotic Scrolls Generated by Memristive Hopfield Neural Network And Its Application In Robot Path Planning

Mingjun Tang, Linyang Guo, Runxian Yang, Chunlin Xu, Lixia Wang
article en

Abstract

Abstract In this paper, a novel three-dimensional space-scroll chaotic attractor are constructed by introducing piece-wise linear memristors into a three-neurons-based Hopfield neural network to simulate the electromagnetic influence on neural dynamics. The dynamical behaviors of the novel memristive Hopfield neural network is discussed by means of numerical methods including the Lyapunov exponent spectrum, bifurcation diagram, phase plots and dynamic maps. Furthermore, we also investigated different neurons subject to the memristive electromagnetic influence, where the two-dimensional grid-scroll chaotic attractors can be generated by one neuron subjects to the electromagnetic influence and three-dimensional space-scroll chaotic attractors can be generated by all of the neurons subject to the memristive electromagnetic influence. Moreover, we present the three-dimensional space-scroll scroll attractor-based chaotic mobile robot system. Superiority of the proposed space-scroll-based chaotic mobile robot system compared to existing methods has been demonstrated through numerical simulations.

Journal of Computational and Nonlinear Dynamics
Yangzhou Polytechnic Institute (CN)
Openalex Percentile: Top 85%
Neural Networks and Applications
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