五惯性 Hopfield 神经网络环形网络的规则和混沌动力学研究:理论、模拟和微控制器仿真

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Jean Baptiste Koinfo, Sridevi Sriram, Kengne Jacques, Anitha Karthikeyan
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引用次数: 0

摘要

本文的研究基于对一个由五个 Hopfield 型惯性神经元组成的同质网络的动力学分析,该网络采用了单向环形耦合拓扑结构。耦合是通过用与前一个神经元成比例的信号扰动下一个神经元的振幅来实现的。该系统由十个耦合的 ODE 组成,所进行的研究让我们发现了几个不寻常和罕见的相关动力学,因此强调这些动力学非常重要。有助于获得上述结果的主要分析工具包括相位图、分岔图和最大李雅普诺夫指数。在这个系统中,我们观察到了同质吸引子和异质吸引子共存、周期加倍危机、平行分支以及通向超混沌多螺旋的路径等现象。所有吸引子都是非隐藏的,因为它们都源自众所周知的平衡点。该系统有 254 个平衡点,其中只有 32 个平衡点会发生霍普夫分岔,随后出现周期加倍,导致合并危机现象,直至最终的超混沌多螺旋吸引子。在相同的参数值(耦合或耗散)下,耦合系数最多有 30 个吸引子共存,耗散最多有 32 个吸引子共存,并通过相位图加以说明。此外,还报告了使用 Pspice 对模型进行的虚拟验证,以及使用 Arduino Mega 2580 微控制器对模型进行的实际验证。它们与数值研究的结果完全一致。对电路能量和无量纲能量进行了估算,并建立了比例关系。这些结果进一步丰富了以往和近期对 Hopfield 型神经网络非线性动力学的研究。此外,值得一提的是,循环耦合类型学可用作在 Hopfield 振荡器中产生多螺旋信号的另一种方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Investigation on the regular and chaotic dynamics of a ring network of five inertial Hopfield neural network: theoretical, analog and microcontroller simulation

Investigation on the regular and chaotic dynamics of a ring network of five inertial Hopfield neural network: theoretical, analog and microcontroller simulation

The studies conducted in this contribution are based on the analysis of the dynamics of a homogeneous network of five inertial neurons of the Hopfield type to which a unidirectional ring coupling topology is applied. The coupling is achieved by perturbing the next neuron's amplitude with a signal proportional to the previous one. The system consists of ten coupled ODEs, and the investigations carried out have allowed us to highlight several unusual and rarely related dynamics, hence the importance of emphasizing them. The main analysis tools that have helped in obtaining the results presented are phase portraits, bifurcation diagrams, and the Maximal Lyapunov exponent. In this system, we have observed phenomena such as the coexistence of homogeneous and heterogeneous attractors, period-doubling crisis, parallel branches, and the path leading to hyperchaotic multi-spiral. All attractors are non-hidden as they originate from well-known equilibrium points. The system has 254 equilibrium points, among which only 32 undergo a Hopf bifurcation followed by period-doubling, leading to a merging crisis phenomenon until the final hyperchaotic multi-spiral attractor. For the same parameter values (coupling or dissipation), a maximum of 30 attractors for the coupling coefficient and 32 attractors for dissipation coexist, and illustrated by the phase portraits. Virtual verification using Pspice and practical verification using an Arduino Mega 2580 microcontroller of the model have also been reported. They are in perfect agreement with the behaviors resulting from numerical investigations. The circuit energy and dimensionless energy has been estimated and the scale relation established. The results presented further enrich previous and recent work in the study of the nonlinear dynamics of Hopfield-type neural networks. Additionally, it is important to mention that cyclic coupling typology may be used as an alternative approach in generating multi-spiral signals in Hopfield oscillators.

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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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