IMPROVED RESULTS ON STABILITY ANALYSIS OF NEURAL NETWORKS WITH TIME-VARYING DELAYS: NOVEL DELAY-DEPENDENT CRITERIA-Reference-Cited by-同舟云学术

IMPROVED RESULTS ON STABILITY ANALYSIS OF NEURAL NETWORKS WITH TIME-VARYING DELAYS: NOVEL DELAY-DEPENDENT CRITERIA

Published:2010-03-30 Issue:08 Volume:24 Page:775-789
ISSN:0217-9849
Container-title:Modern Physics Letters B
language:en
Short-container-title:Mod. Phys. Lett. B

Author:

KWON O. M.¹,LEE S. M.²,PARK JU H.³

Affiliation:

1. School of Electrical Engineering, Chungbuk National University, 410 SungBong-Ro, Heungduk-gu, Cheongju 361-763, Republic of Korea

2. Department of Electronic Engineering, Daegu University, Gyungsan 712-714, Republic of Korea

3. Department of Electrical Engineering, Yeungnam University, 214-1 Dae-Dong, Kyongsan 712-749, Republic of Korea

Abstract

In this paper, the problem of stability analysis of neural networks with discrete time-varying delays is considered. By constructing a new Lyapunov functional and some novel analysis techniques, new delay-dependent criteria for checking the asymptotic stability of the neural networks are established. The criteria are presented in terms of linear matrix inequalities, which can be easily solved and checked by various convex optimization algorithms. Three numerical examples are included to show the superiority of our results.

Publisher

World Scientific Pub Co Pte Lt

Subject

Condensed Matter Physics,Statistical and Nonlinear Physics

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0217984910022858

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