Existence and exponential stability of anti-periodic solutions for interval general bidirectional associative memory neural networks with multiple delays

Advances in Difference Equations

Xiaofei Li¹  Jianzhong Feng¹  Songbo Hu²  Deng Ding² 

[1]Faculty of Science and Technology, University of Macau, Macau, P.R. China

[2]School of Information and Mathematics, Yangtze University, Jingzhou, P.R. China

关键词: bidirectional associative memory neural networks;    anti-periodic solution;    exponential stability;    delay;    34C25;    34K13;    34K25;   

DOI  :  10.1186/s13662-016-0882-7

学科分类：数学（综合）

来源: SpringerOpen

【 摘 要 】

In this article, we will consider the a class of interval general bidirectional associative memory (BAM) neural networks with multiple delays. Based on the fundamental solution matrix of coefficients, inequality technique and Lyapunov method, we derive a series of sufficient conditions to ensure the existence and exponential stability of anti-periodic solutions of the neural networks with multiple delays. Our findings are new and complement some previously known studies.

【 授权许可】

CC BY