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
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
โ 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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โฆ 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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