Stability analysis of almost periodic solutions for delayed neural networks without global Lipschitz activation functions

Jun Zhou, Weirui Zhao, Xiaohong Lv and Huaping Zhu

Mathematics and Computers in Simulation (MATCOM), 2011, vol. 81, issue 11, 2440-2455

Abstract: In this paper, the existence and local exponential stability of the almost periodic solutions for recurrent neural networks with mixed delays have been investigated. By applying Dini derivative and introducing many real parameters, and estimating the upper bound of solutions of the system, a series of new and useful criteria on the existence and local exponential stability of almost periodic for general delayed neural networks without global Lipschitz activation functions have been derived. Those results obtained in this paper extend and generalize the corresponding results existing in the previous literature. Two examples and numerical simulations are given to illustrate our theory.

Keywords: Neural networks; Delays; Local exponential stability; Almost periodic solution (search for similar items in EconPapers)
Date: 2011
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:81:y:2011:i:11:p:2440-2455

DOI: 10.1016/j.matcom.2011.03.009

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