Global Exponential Stability of Discrete-Time Neural Networks with Time-Varying Delays | Zendy

S. Udpin | Zendy; Piyapong Niamsup | Zendy

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Global Exponential Stability of Discrete-Time Neural Networks with Time-Varying Delays

Author(s) -

S. Udpin,

Piyapong Niamsup

Publication year - 2013

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 - 10.1155/2013/325752

Subject(s) - discrete time and continuous time , artificial neural network , nonlinear system , stability (learning theory) , control theory (sociology) , exponential stability , mathematics , computer science , control (management) , artificial intelligence , statistics , physics , quantum mechanics , machine learning

This paper presents some global stability criteria of discrete-time neural networks with time-varying delays. Based on a discrete-type inequality, a new global stability condition for nonlinear difference equation is derived. We consider nonlinear discrete systems with time-varying delays and independence of delay time. Numerical examples are given to illustrate the effectiveness of our theoretical results

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