Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/86189
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Type: Journal article
Title: Improved free-weighting matrix approach for stability analysis of discrete-time recurrent neural networks with time-varying delay
Author: Wu, M.
Liu, F.
Shi, P.
He, Y.
Yokoyama, R.
Citation: IEEE Transactions on Circuits and Systems, Part 2: Express Briefs, 2008; 55(7):690-694
Publisher: Institute of Electrical and Electronics Engineers
Issue Date: 2008
ISSN: 1549-7747
Statement of
Responsibility: 
Min Wu, Fang Liu, Peng Shi, Yong He and Ryuichi Yokoyama
Abstract: This paper deals with the problem of exponential stability for a class of discrete-time recurrent neural networks with time-varying delay by employing an improved free-weighting matrix approach. The relationship among the time-varying delay, its upper bound and their difference is taken into account. As a result, a new and less conservative delay-dependent stability criterion is obtained without ignoring any useful terms on the difference of a Lyapunov function, which is expressed in terms of linear matrix inequalities. Finally, numerical examples are given to demonstrate the effectiveness of the proposed techniques.
Keywords: Discrete-time recurrent neural networks; time-varying delay; delay-dependent stability; Lyapunov function; linear matrix inequalities (LMIs)
Rights: © 2008 IEEE
RMID: 0020128112
DOI: 10.1109/TCSII.2008.921597
Appears in Collections:Electrical and Electronic Engineering publications

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