Global asymptotic stability of piecewise homogeneous Markovian jump BAM neural networks with discrete and distributed time-varying delays

Advances in Difference Equations

Wu Wen¹  Jia Xu²  Nan Zhou³  Shouming Zhong⁴  Yuanhua Du⁴ 

[1] Department of Academic Affairs Office, Sichuan University of Arts and Science of China, Dazhou, P.R. China;Department of Financial Affairs Office, Sichuan University of Arts and Science of China, Dazhou, P.R. China;School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu, P.R. China;School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, P.R. China

关键词: BAM neural networks;    linear matrix inequality;    piecewise homogeneous;    Markovian jump;    distributed;    time-varying delays;    Lyapunov-Krasovskii functional;   

DOI  :  10.1186/s13662-016-0758-x

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this paper, the issue of a global asymptotic stability analysis is developed for piecewise homogeneous Markovian jump BAM neural networks with mixed time delays. By establishing the Lyapunov functional, using mode-dependent discrete delay and applying the linear matrix inequality (LMI) method, a novel sufficient condition is obtained to guarantee the stability of the considered system. A numerical example is provided to demonstrate the feasibility and effectiveness of the proposed results.

【 授权许可】

CC BY