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.
"Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays." Abstr. Appl. Anal. 2012 (SI04) 1 - 12, 2012. https://doi.org/10.1155/2012/372324