Input‐to‐State Stability for Dynamical Neural Networks with Time‐Varying Delays
Weisong Zhou, Zhichun Yang · Abstract and Applied Analysis · 2012
A class of dynamical neural network models with time‐varying delays is considered. By employing the Lyapunov‐Krasovskii functional method and linear matrix inequalities (LMIs) technique, some new sufficient conditions ensuring the input‐to‐state stability (ISS) property of the nonlinear network systems are obtained. Finally, numerical examples are provided to illustrate the efficiency of the derived results.