Stability Criteria for Stochastic Recurrent Neural Networks with Two Time-Varying Delays and Impulses | Zendy

R. Raja | Zendy; S. Marshal Anthoni | Zendy

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Stability Criteria for Stochastic Recurrent Neural Networks with Two Time-Varying Delays and Impulses

Author(s) -

R. Raja,

S. Marshal Anthoni

Publication year - 2010

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/514-831

Subject(s) - computer science , stability (learning theory) , artificial neural network , artificial intelligence , control theory (sociology) , machine learning , control (management)

This paper is concerned with a stability problem for a class of stochastic recurrent impulsive neural networks with both discrete and distributed time-varying delays. Based on Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of impulsive neural networks. Two numerical examples are given to illustrate the effectiveness of the stability results.

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