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Zbl 1211.93109
Ahn, Choon Ki
Passive learning and input-to-state stability of switched Hopfield neural networks with time-delay. (English)
[J] Inf. Sci. 180, No. 23, 4582-4594 (2010). ISSN 0020-0255

Summary: 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.

MSC 2000:: *93D21 Adaptive and robust stabilization
68T05 Learning and adaptive systems

Keywords: passive weight learning law; switched Hopfield neural networks; input-to-state stability (ISS); linear matrix inequality (LMI); Lyapunov-Krasovskii stability theory

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Zentralblatt MATH Berlin [Germany]