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Exponential stability of Hopfield neural networks with time‐varying delays via impulsive control
Author(s) -
Li Xiaodi
Publication year - 2010
Publication title -
mathematical methods in the applied sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.719
H-Index - 65
eISSN - 1099-1476
pISSN - 0170-4214
DOI - 10.1002/mma.1278
Subject(s) - exponential stability , mathematics , control theory (sociology) , stability (learning theory) , exponential function , artificial neural network , hopfield network , lyapunov function , exponential growth , control (management) , computer science , mathematical analysis , artificial intelligence , nonlinear system , machine learning , physics , quantum mechanics
In this paper, by utilizing the Lyapunov functionals, the analysis method and the impulsive control, we analyze the exponential stability of Hopfield neural networks with time‐varying delays. A new criterion on the exponential stabilization by impulses and the exponential stabilization by periodic impulses is gained. We can see that impulses do contribution to the system's exponential stability. Two examples are given to illustrate the effectiveness of our result. Copyright © 2010 John Wiley & Sons, Ltd.