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Improved delay-dependent exponential stability criteria for discrete-time recurrent neural networks with time-varying delays
- Source :
-
Neurocomputing . Dec2008, Vol. 72 Issue 1-3, p321-330. 10p. - Publication Year :
- 2008
-
Abstract
- Abstract: This paper is concerned with the problem of stability analysis for a class of discrete-time recurrent neural networks with time-varying delays. Under a weak assumption on the activation functions and using a new Lyapunov functional, a delay-dependent condition guaranteeing the global exponential stability of the concerned neural network is obtained in terms of a linear matrix inequality. It is shown that this stability condition is less conservative than some previous ones in the literature. When norm-bounded parameter uncertainties appear in a delayed discrete-time recurrent neural network, a delay-dependent robust exponential stability criterion is also presented. Numerical examples are provided to demonstrate the effectiveness of the proposed method. [Copyright &y& Elsevier]
Details
- Language :
- English
- ISSN :
- 09252312
- Volume :
- 72
- Issue :
- 1-3
- Database :
- Academic Search Index
- Journal :
- Neurocomputing
- Publication Type :
- Academic Journal
- Accession number :
- 35326924
- Full Text :
- https://doi.org/10.1016/j.neucom.2008.01.006