Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays | Zendy

Yin Xing | Zendy; Jun Li | Zendy; Weigen Wu | Zendy; Qiranrong Tan | Zendy

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Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays

Author(s) -

Yin Xing,

Jun Li,

Weigen Wu,

Qiranrong Tan

Publication year - 2011

Publication title -

discrete dynamics in nature and society

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.264

H-Index - 39

eISSN - 1607-887X

pISSN - 1026-0226

DOI - 10.1155/2011/325371

Subject(s) - control theory (sociology) , artificial neural network , stability (learning theory) , weighting , recurrent neural network , discrete time and continuous time , computer science , quadratic equation , linear matrix inequality , state (computer science) , mathematics , mathematical optimization , algorithm , control (management) , artificial intelligence , medicine , statistics , geometry , machine learning , radiology

This paper deals with the problem of delay-dependent stability criterion ofuncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF) and free-weighting matrix approach (FWM), some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria

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