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
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
Journal title :
Mathematics and Computers in Simulation