AUTHOR=Liu Mei , Jiang Haijun , Hu Cheng , Lu Binglong , Li Zhanfeng 

TITLE=Novel Global Asymptotic Stability and Dissipativity Criteria of BAM Neural Networks With Delays

JOURNAL=Frontiers in Physics

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/physics/articles/10.3389/fphy.2022.898589

DOI=10.3389/fphy.2022.898589

ISSN=2296-424X

ABSTRACT=In this paper, issues of both stability  and dissipativity for a class of bidirectional associative memory (BAM) neural networks with time delays are investigated. By using generalized Halanay inequalities and constructing suitable Lyapunov functional, some new criteria are obtained for the global asymptotic stability of BAM neural networks with time delays. And without assuming  differentiability and boundedness of activation functions, some new sufficient conditions for checking the dissipativity of the addressed neural networks are established by using matrix theory, inner product properties. The derived results extend and improve some previous known works  on these problems for conventional BAM neural networks. Finally, numerical examples and their simulations are given to show the effectiveness of the theoretical results.