Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Journal article
Title: Exponential stability analysis for neural networks with time-varying delay
Author: Wu, M.
Liu, F.
Shi, P.
He, Y.
Yokoyama, R.
Citation: IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, 2008; 38(4):1152-1156
Publisher: IEEE-Inst Electrical Electronics Engineers Inc
Issue Date: 2008
ISSN: 1083-4419
Statement of
Min Wu, Fang Liu, Peng Shi, Yong He, and Ryuichi Yokoyama
Abstract: This correspondence paper focuses on the problem of exponential stability for neural networks with a time-varying delay. The relationship among the time-varying delay, its upper bound, and their difference is taken into account. As a result, an improved linear-matrix-inequality-based delay-dependent exponential stability criterion is obtained without ignoring any terms in the derivative of Lyapunov-Krasovskii functional. Two numerical examples are given to demonstrate its effectiveness.
Keywords: Algorithms; Neural Networks (Computer); Models, Theoretical; Computer Simulation
Rights: © 2008 IEEE
RMID: 0020128058
DOI: 10.1109/TSMCB.2008.915652
Appears in Collections:Electrical and Electronic Engineering publications

Files in This Item:
There are no files associated with this item.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.