Novel robust stability criteria of neutral-type bidirectional associative memory neural networks
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چکیده
The existence, uniqueness and global robust exponential stability is analyzed for a class of uncertain neutral-type bidirectional associative memory (BAM) neural networks with time-varying delays. Without assuming the boundedness of the activation functions, by constructing a novel class of augmented LyapunovKrasovskii functional, new relaxed delay-dependent stability criteria of the unique equilibrium point are presented in terms of linear matrix inequalities (LMIs). Following the idea of convex combination and free-weighting matrices method, less conservative results are obtained. Two examples are given to illustrate the effectiveness of our proposed conditions.
منابع مشابه
Novel Robust Stability Criteria of Neutral-type Bidirectional Associative Memory Neural Networks
The global robust exponential stability is analyzed for a class of uncertain neutral-typebidirectional associative memory (BAM) neural networks with time-varying delays. Without assumingthe boundedness of the activation functions, by constructing a novel class of augmented Lyapunov-Krasovskii functional, new relaxed delay-dependent stability criteria of the unique equilibrium point are presente...
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تاریخ انتشار 2014