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具有状态相关切换规则的切换神经网络的多稳定性和固定时间多同步。

Multistability and fixed-time multisynchronization of switched neural networks with state-dependent switching rules.

机构信息

School of Mathematics and Statistics, Guizhou University, Guiyang 550025, China.

School of Mathematics, Hunan University, Changsha 410082, China.

出版信息

Neural Netw. 2024 Dec;180:106713. doi: 10.1016/j.neunet.2024.106713. Epub 2024 Sep 7.

Abstract

This paper presents theoretical results on the multistability and fixed-time synchronization of switched neural networks with multiple almost-periodic solutions and state-dependent switching rules. It is shown herein that the number, location, and stability of the almost-periodic solutions of the switched neural networks can be characterized by making use of the state-space partition. Two sets of sufficient conditions are derived to ascertain the existence of 3 exponentially stable almost-periodic solutions. Subsequently, this paper introduces the novel concept of fixed-time multisynchronization in switched neural networks associated with a range of almost-periodic parameters within multiple stable equilibrium states for the first time. Based on the multistability results, it is demonstrated that there are 3 synchronization manifolds, wherein n is the number of neurons. Additionally, an estimation for the settling time required for drive-response switched neural networks to achieve synchronization is provided. It should be noted that this paper considers stable equilibrium points (static multisynchronization), stable almost-periodic orbits (dynamical multisynchronization), and hybrid stable equilibrium states (hybrid multisynchronization) as special cases of multistability (multisynchronization). Two numerical examples are elaborated to substantiate the theoretical results.

摘要

本文提出了关于具有多个概周期解和状态相关切换规则的切换神经网络的多稳定性和固定时间同步的理论结果。本文表明,可以通过状态空间分区来表征切换神经网络的概周期解的数量、位置和稳定性。推导出了两组充分条件,以确定存在 3 个指数稳定的概周期解。随后,本文首次在与多个稳定平衡点相关的切换神经网络中引入了固定时间多同步的新概念,其对应的几乎周期参数范围较广。基于多稳定性结果,证明了存在 3 个同步流形,其中 n 是神经元的数量。此外,还提供了驱动-响应切换神经网络实现同步所需的 settling 时间的估计。需要注意的是,本文将稳定平衡点(静态多同步)、稳定概周期轨道(动态多同步)和混合稳定平衡点(混合多同步)视为多稳定性(多同步)的特例。通过两个数值示例验证了理论结果。

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