切换拓扑下基于Lp稳定性的延迟多权神经网络同步

IF 2.7 3区数学 Q1 MATHEMATICS, APPLIED

Physica D: Nonlinear Phenomena Pub Date : 2025-02-22 DOI:10.1016/j.physd.2025.134577

Yunxiao Jia, Xiaona Yang, Xian Zhang

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引用次数: 0

摘要

研究了切换拓扑下延时多权神经网络基于Lp稳定性的同步问题。所涉及的延迟包括时变泄漏、传输和分布式延迟。首先，设计了一种新的控制器，以保证驱动和响应多权神经网络之间基于Lp稳定的同步。其次，研究了所考虑误差系统解的性质，为获得基于Lp稳定同步的新判据奠定了基础。与已有的判据相比，所得到的判据只包含少量简单的线性标量不等式，从而大大减少了计算量。最后，以通信网络为例，验证了所得到的基于Lp稳定性的同步准则的适用性。值得注意的是，本文首次解决了切换拓扑下延迟多权神经网络基于Lp稳定的同步控制问题，所提方法直接基于Lp稳定同步的定义，易于推广到一些切换延迟系统模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Lp stability-based synchronization of delayed multi-weight neural networks under switching topologies

In this paper, the

L_{p}

stability-based synchronization problem of delayed multi-weight neural networks under switching topologies is investigated. The involved delays include time-varying leakage, transmission and distributed delays. Firstly, a novel controller is designed to ensure

L_{p}

stability-based synchronization between the drive and response multi-weight neural networks. Secondly, a property of solutions of the considered error system is investigated, which forms a basis of obtaining a new criterion of

L_{p}

stability-based synchronization. In contrast to the existing ones, the obtained criterion comprises just a small number of simple linear scalar inequalities, thereby amount of computations is greatly reduced. Finally, a numerical example related to communication networks is presented to demonstrate the applicability of the obtained

L_{p}

stability-based synchronization criterion. It is worth noting that the

L_{p}

stability-based synchronization control problem of delayed multi-weight neural networks under switching topologies is solved for the first time, and the proposed method is directly based on the definitions of

L_{p}

stability-based synchronization, which is easily extended to some switching delayed system models.

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来源期刊

Physica D: Nonlinear Phenomena 物理-物理：数学物理

CiteScore

7.30

自引率

7.50%

发文量

213

审稿时长

65 days

期刊介绍： Physica D (Nonlinear Phenomena) publishes research and review articles reporting on experimental and theoretical works, techniques and ideas that advance the understanding of nonlinear phenomena. Topics encompass wave motion in physical, chemical and biological systems; physical or biological phenomena governed by nonlinear field equations, including hydrodynamics and turbulence; pattern formation and cooperative phenomena; instability, bifurcations, chaos, and space-time disorder; integrable/Hamiltonian systems; asymptotic analysis and, more generally, mathematical methods for nonlinear systems.