Global Robust Stability of General Recurrent Neural Networks with Time-Varying Delays
This paper is devoted to global robust stability analysis of the general recurrent neural networks with time-varying parametric uncertainty and time-varying delays. To remove the dependence on the size of time-delays, Lyapunov-Razumikhin stability theorem and LMI approach are applied to derive the global robust stability conditions for the neural networks. Then delay-dependent global robust stability criteria are developed based on integrating Lyapunov-Krasovskii functional method and LMI approach. These stability criteria are in term of the solvability of linear matrix inequalities.
KeywordsLinear Matrix Inequality Robust Stability Cellular Neural Network Delayed Neural Network Global Robust Stability
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