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Delay‐dependent robust stability analysis for interval neural networks with time‐varying delay
Author(s) -
Liu Fang,
Wu Min,
He Yong,
Zhou Yicheng,
Yokoyama Ryuichi
Publication year - 2011
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.20667
Subject(s) - interval (graph theory) , stability (learning theory) , linear matrix inequality , control theory (sociology) , artificial neural network , upper and lower bounds , mathematics , computer science , mathematical optimization , artificial intelligence , mathematical analysis , control (management) , machine learning , combinatorics
This article deals with the problem of robust stability for interval neural networks with time‐varying delay. By constructing an appropriate Lyapunov–Krasovskii functional, using the S‐procedure and taking the relationship among the time‐varying delay, its upper bound and their difference into account, some linear matrix inequality(LMI) ‐based delay‐dependent stability criteria are obtained without ignoring any terms in the derivative of the Lyapunov–Krasovskii functional. Finally, two numerical examples are given to demonstrate the effectiveness and benefits of the proposed method. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.