IEEE Trans Neural Netw Learn Syst - Stochastic Stability of Delayed Neural Networks With Local Impulsive Effects.

Tópicos

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Resumo

In this paper, the stability problem is studied for a class of stochastic neural networks (NNs) with local impulsive effects. The impulsive effects considered can be not only nonidentical in different dimensions of the system state but also various at distinct impulsive instants. Hence, the impulses here can encompass several typical impulses in NNs. The aim of this paper is to derive stability criteria such that stochastic NNs with local impulsive effects are exponentially stable in mean square. By means of the mathematical induction method, several easy-to-check conditions are obtained to ensure the mean square stability of NNs. Three examples are given to show the effectiveness of the proposed stability criterion.

Resumo Limpo

paper stabil problem studi class stochast neural network nns local impuls effect impuls effect consid can nonident differ dimens system state also various distinct impuls instant henc impuls can encompass sever typic impuls nns aim paper deriv stabil criteria stochast nns local impuls effect exponenti stabl mean squar mean mathemat induct method sever easytocheck condit obtain ensur mean squar stabil nns three exampl given show effect propos stabil criterion

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