Input‐to‐State Stability for Dynamical Neural Networks with Time‐Varying Delays
Weisong Zhou and
Zhichun Yang
Abstract and Applied Analysis, 2012, vol. 2012, issue 1
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
References: Add references at CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1155/2012/372324
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2012:y:2012:i:1:n:372324
Access Statistics for this article
More articles in Abstract and Applied Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().