New delay-dependent exponential stability criteria for neural networks with discrete and distributed time-varying delays

Authors:
Junkang Tian;Shouming Zhong
Affiliations:
School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China and Key Laboratory for Neuroinformation of Ministry of Education, Unive ...;School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, PR China and Key Laboratory for Neuroinformation of Ministry of Education, Unive ...
Venue:
Neurocomputing
Year:
2011

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Abstract

In this paper, the problem of exponential stability criteria for neural networks with discrete and distributed time-varying delays are considered. By dividing the discrete delay interval into multiple segments and choosing a new class of Lyapunov functional which contains tripe-integral terms, some new delay-dependent stability criteria are derived in terms of linear matrix inequalities. The obtained criteria are less conservative because free-weighting matrices method and a convex optimization approach are considered. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.