Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
412998 | Neurocomputing | 2009 | 6 Pages |
Abstract
This paper is concerned with the problem of robust exponential stability analysis for uncertain discrete recurrent neural networks with time-varying delays. In terms of linear matrix inequality (LMI) approach, some novel stability conditions are proposed via a new Lyapunov function. Neither any model transformation nor free-weighting matrices are employed in our theoretical derivation. The established stability criteria significantly improve and simplify some existing stability conditions. Numerical examples are given to demonstrate the effectiveness of the proposed methods.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhengguang Wu, Hongye Su, Jian Chu, Wuneng Zhou,