Passive learning and input-to-state stability of switched Hopfield neural networks with time-delay

Authors:
Choon Ki Ahn
Affiliations:
Department of Automotive Engineering, Seoul National University of Technology, 172 Gongneung 2-dong, Nowon-gu, Seoul 139-743, Republic of Korea
Venue:
Information Sciences: an International Journal
Year:
2010

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Abstract

In this paper, we propose a new passive weight learning law for switched Hopfield neural networks with time-delay under parametric uncertainty. Based on the proposed passive learning law, some new stability results, such as asymptotical stability, input-to-state stability (ISS), and bounded input-bounded output (BIBO) stability, are presented. An existence condition for the passive weight learning law of switched Hopfield neural networks is expressed in terms of strict linear matrix inequality (LMI). Finally, numerical examples are provided to illustrate our results.