Input-to-State Stability for Dynamical Neural Networks with Time-Varying Delays

Weisong Zhou and Zhichun Yang

Abstract and Applied Analysis, 2012, vol. 2012, 1-12

Abstract:

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.

Date: 2012
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlaaa:372324

DOI: 10.1155/2012/372324

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