An analysis on the global exponential stability and the existence of periodic solutions for non-autonomous hybrid BAM neural networks with distributed delays and impulses

Authors:
Yao-tang Li;Jiyu Wang
Affiliations:
School of Mathematics and Statistics, Yunnan University, Kunming, Yunnan, 650091, PR China;School of Mathematics and Statistics, Yunnan University, Kunming, Yunnan, 650091, PR China
Venue:
Computers & Mathematics with Applications
Year:
2008

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Abstract

In this paper, by utilizing the Lyapunov functional method, applying M-matrix, Young inequality technique and other analysis techniques, we analyze the exponential stability and the existence of periodic solutions for non-autonomous hybrid BAM neural networks with distributed delays and impulses. Sufficient conditions are obtained for the global exponential stability and the existence of periodic solutions for non-autonomous hybrid bidirectional associative memory (BAM) neural networks with Lipschitzian activation functions without assuming their boundedness, monotonicity or differentiability and subjected to impulsive state displacements at fixed instants of time. Finally, two examples are also provided to demonstrate the effectiveness of the results obtained.