Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays | Zendy

Yuanfu Shao | Zendy; Changjin Xu | Zendy; Qianhong Zhang | Zendy

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Globally Exponential Stability of Periodic Solutions to Impulsive Neural Networks with Time-Varying Delays

Author(s) -

Yuanfu Shao,

Changjin Xu,

Qianhong Zhang

Publication year - 2012

Publication title -

abstract and applied analysis

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.228

H-Index - 56

eISSN - 1687-0409

pISSN - 1085-3375

DOI - 10.1155/2012/358362

Subject(s) - mathematics , exponential stability , artificial neural network , stability (learning theory) , control theory (sociology) , lyapunov function , exponential function , exponential growth , mathematical analysis , computer science , nonlinear system , artificial intelligence , machine learning , physics , control (management) , quantum mechanics

By using Schaeffer's theorem and Lyapunov functional, sufficient conditions of the existence and globally exponential stability of positive periodic solution to an impulsive neural network with time-varying delays are established. Applications, examples, and numerical analysis are given to illustrate the effectiveness of the main results

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