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research-article

Improved results on finite-time stability analysis of neural networks with time-varying delays

[+] Author and Article Information
Saravanan Shanmugam

Department of Mathematics, Thiruvalluvar University, Vellore-632 115, Tamilnadu, India
saravanantvu@gmail.com

M.Syed Ali

Department of Mathematics, Thiruvalluvar University, Vellore-632 115, Tamilnadu, India
syedgru@gmail.com

1Corresponding author.

ASME doi:10.1115/1.4039667 History: Received June 30, 2017; Revised March 02, 2018

Abstract

In this paper investigates the issue of finite-time stability analysis of time-delayed neural networks. By introducing a new Lyapunov functional which uses the information on the delay sufficiently and an augmented Lyapunov functional which contains some triple integral terms. Some improved delay-dependent stability criteria are derived using the Jensen's inequality, reciprocally convex combination methods. Then the finite-time stability conditions are solving by the Linear matrix inequalities (LMIs). Numerical examples are finally presented to verify the effectiveness of the obtained results

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