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A New Delay-Dependent Approach to Robust Stability for Uncertain Hybrid Bidirectional Associative Memory Neural Networks with Time-Varying Delays

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3 Author(s)
Chien-Yu Lu ; National Chandhua University of Education Taiwan ; Te-Jen Su ; Wen-Jye Shyr

This paper considers the problem of global robust stability analysis for a class of bidirectional associative memory time-varying delayed neural networks with norm-bounded time-varying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing some relaxation matrices which can be chosen properly to lead to a less conservative result. Numerical examples are given to illustrate the significant improvement on the conservativeness of the delay bound over some reported results in the literature

Published in:

First International Conference on Innovative Computing, Information and Control - Volume I (ICICIC'06)  (Volume:1 )

Date of Conference:

Aug. 30 2006-Sept. 1 2006