Global Asymptotical Stability in Neutral-Type Delayed Neural Networks with Reaction-Diffusion Terms
In this paper, the global uniform asymptotical stability is studied for delayed neutral-type neural networks by constructing appropriate Lyapunov functional and using the linear matrix inequality (LMI) approach. The main condition given in this paper is dependent on the size of the measure of the space, which is usually less conservative than space-independent ones. Finally, a numerical example is provided to demonstrate the effectiveness and applicability of the proposed criteria.
KeywordsNeural Network Linear Matrix Inequality Exponential Stability Recurrent Neural Network Cellular Neural Network
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