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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

โœ Scribed by Yao-tang Li; Jiyu Wang


Publisher
Elsevier Science
Year
2008
Tongue
English
Weight
326 KB
Volume
56
Category
Article
ISSN
0898-1221

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โœฆ Synopsis


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 nonautonomous 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.


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โœ Zhengqiu Zhang; Kaiyu Liu ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 486 KB

In this paper, we first investigate the existence of a periodic solution to interval general bidirectional associative memory (BAM) neural networks with multiple delays on time scales by the continuation theorem of coincidence degree theory. Then, by constructing a Lyapunov functional, we discuss th