Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays | Zendy

Yingxin Guo | Zendy; Mingzhi Xue | Zendy

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Periodic Solutions and Exponential Stability of a Class of Neural Networks with Time-Varying Delays

Author(s) -

Yingxin Guo,

Mingzhi Xue

Publication year - 2009

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 - 10.1155/2009/415786

Subject(s) - class (philosophy) , exponential stability , artificial neural network , stability (learning theory) , computer science , control theory (sociology) , exponential function , mathematics , point (geometry) , fixed point theorem , discrete mathematics , artificial intelligence , mathematical analysis , nonlinear system , machine learning , control (management) , physics , geometry , quantum mechanics

Employing fixed point theorem, we make a further investigation of a class ofneural networks with delays in this paper. A family of sufficient conditions is given forchecking global exponential stability. These results have important leading significance inthe design and applications of globally stable neural networks with delays. Our resultsextend and improve some earlier publications

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