Title of article
Stability analysis of almost periodic solutions for delayed neural networks without global Lipschitz activation functions Original Research Article
Author/Authors
Jun Zhou، نويسنده , , Weirui Zhao، نويسنده , , Guanwei Luo and Xiaohong Lv، نويسنده , , Huaping Zhu، نويسنده ,
Issue Information
روزنامه با شماره پیاپی سال 2011
Pages
16
From page
2440
To page
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
Local exponential stability , Almost periodic solution , Neural networks , Delays
Journal title
Mathematics and Computers in Simulation
Serial Year
2011
Journal title
Mathematics and Computers in Simulation
Record number
855168
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