New inequality-based approach to passivity analysis of neural networks with interval time-varying delay

NEUROCOMPUTING

卷:194

Article

Thuan, M. V.¹  Trinh, H.²  Hien, L. V.³ 

[1] Thainguyen Univ Sci, Dept Math & Informat, Thainguyen, Vietnam

[2] Deakin Univ, Sch Engn, Geelong, Vic 3217, Australia

[3] Hanoi Natl Univ Educ, Dept Math, Hanoi, Vietnam

关键词: Passivity;    Neural networks;    Time-varying delay;    Jensen inequality;    Linear matrix inequality;   

DOI  :  10.1016/j.neucom.2016.02.051

来源: Elsevier

【 摘 要 】

This paper is concerned with the problem of passivity analysis of neural networks with an interval time varying delay. Unlike existing results in the literature, the time-delay considered in this paper is subjected to interval time-varying without any restriction on the rate of change. Based on novel refined Jensen inequalities and by constructing an improved Lyapunov-Krasovskii functional (LKF), which fully utilizes information of the neuron activation functions, new delay-dependent conditions that ensure the passivity of the network are derived in terms of tractable linear matrix inequalities (LMIs) which can be effectively solved by various computational tools. The effectiveness and improvement over existing results of the proposed method in this paper are illustrated through numerical examples. (C) 2016 Elsevier B.V. All rights reserved.

【 授权许可】

Free