A Delay Decomposition Approach for Robust Dissipativity and Passivity Analysis of Neutral-Type Neural Networks with Leakage Time-Varying Delay

被引:13
作者
Nagamani, Gnaneswaran [1 ]
Radhika, Thirunavukkarasu [1 ]
Balasubramaniam, Pagavathi [1 ]
机构
[1] Deemed Univ, Gandhigram Rural Inst, Dept Math, Gandhigram 624302, Tamil Nadu, India
关键词
dissipativity; leakage time-varying delay; linear matrix inequality; Lyapunov method; neutral-type neural networks; ASYMPTOTIC STABILITY-CRITERIA; GLOBAL STABILITY; STATE ESTIMATOR; DISCRETE; SYSTEMS; SYNCHRONIZATION; PASSIFICATION; DESIGN;
D O I
10.1002/cplx.21652
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This article presents the robust dissipativity and passivity analysis of neutral-type neural networks with leakage time-varying delay via delay decomposition approach. Using delay decomposition technique, new delay-dependent criteria ensuring the considered system to be (Q, R, S)-gamma dissipative are established in terms of strict linear matrix inequalities. A new Lyapunov-Krasovskii functional is constructed by dividing the discrete and neutral delay intervals into m and l segments, respectively, and choosing different Lyapunov functionals to different segments. Further, the dissipativity behaviors of neural networks which are affected due to the sensitiveness of the time delay in the leakage term have been taken into account. Finally, numerical examples are provided to show the effectiveness of the proposed method. (C) 2015 Wiley Periodicals, Inc.
引用
收藏
页码:248 / 264
页数:17
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