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具有反应扩散的马尔可夫跳跃合作竞争网络的H二分同步控制

H Bipartite Synchronization Control of Markov Jump Cooperation-Competition Networks With Reaction-Diffusions.

作者信息

Shen Hao, Wang Xuelian, Duan Peiyong, Cao Jinde, Wang Jing

出版信息

IEEE Trans Cybern. 2023 Oct;53(10):6626-6635. doi: 10.1109/TCYB.2022.3195781. Epub 2023 Sep 15.

Abstract

This article is concerned with the bipartite synchronization problem of coupled switching neural networks with cooperative-competitive interactions and reaction-diffusion terms. Different from the existing literature, the networked systems under investigation possess the relationship of cooperation and competition among nodes. Notably, the switching topology is described by a signed graph subject to the Markov jump process with the coexistence of positive and negative interaction weights. Specifically, a positive weight indicates an alliance relationship between two nodes and a negative one shows an adversary relationship. This article aims to design a bipartite synchronization controller for the aforementioned networks with the switching topology such that a prescribed H bipartite synchronization is satisfied. Then, some sufficient criteria to ensure the stochastic stability of bipartite synchronization error systems are established in view of an appropriate Lyapunov function. Finally, two simulation examples are presented to verify the validity of the proposed bipartite synchronization control method.

摘要

本文研究具有合作竞争相互作用和反应扩散项的耦合切换神经网络的二分同步问题。与现有文献不同,所研究的网络系统节点之间存在合作与竞争关系。值得注意的是,切换拓扑由一个带符号图描述,该图服从具有正负交互权重共存的马尔可夫跳跃过程。具体而言,正权重表示两个节点之间的联盟关系,负权重表示敌对关系。本文旨在为上述具有切换拓扑的网络设计一个二分同步控制器,使得满足规定的H二分同步。然后,基于适当的李雅普诺夫函数,建立了一些确保二分同步误差系统随机稳定性的充分准则。最后,给出两个仿真例子以验证所提出的二分同步控制方法的有效性。

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