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Global exponential stability of a class of impulsive cellular neural networks with supremums
Author(s) -
Stamova Ivanka,
Stamov Trayan,
Li Xiaodi
Publication year - 2014
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2440
Subject(s) - exponential stability , cellular neural network , class (philosophy) , stability (learning theory) , lyapunov function , artificial neural network , control theory (sociology) , computer science , mathematics , exponential growth , mathematical optimization , control (management) , artificial intelligence , nonlinear system , machine learning , mathematical analysis , quantum mechanics , physics
SUMMARY In this paper, we study the problem of global exponential stability for impulsive cellular neural networks with time‐varying delays and supremums. Using Young's inequality and Lyapunov‐like functions, new stability criteria are proved. Because supremums and impulses are relevant in various contexts, including problems in the theory of automatic control, our results can be applied in the qualitative investigations of many practical problems of diverse interest. Copyright © 2013 John Wiley & Sons, Ltd.