Novel Delay-Dependent Stability Criteria for Discrete-Time Neural Networks with Time-Varying Delay

被引：2
|
作者：
Stojanovic, Sreten [1 ]
Stojanovic, Milan [2 ,3 ]
Stevanovic, Milos [1 ]
机构：
[1] Univ Nis, Fac Technol, Dept Engn Sci & Appl Math, Bulevar Oslobodjenja 124, Leskovac 16000, Serbia
[2] Univ Belgrade, Sch Elect Engn, Dept Syst Control & Signal Proc, Bulevar Kralja Aleksandra 73, Belgrade 11000, Serbia
[3] Vlatacom Inst Ltd, Bulevar Milutina Milankovica 5, Belgrade 11000, Serbia
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2018年 / 2018卷
关键词：
LYAPUNOV-KRASOVSKII FUNCTIONALS; SUMMATION INEQUALITY; SYSTEMS; PASSIVITY;
D O I：
10.1155/2018/5397870
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
The delay-dependent stability problem is investigated for discrete-time neural networks with time-varying delays. A new augmented Lyapunov-Krasovskii functional (LKF) with single and double summation terms and several augmented vectors is proposed by decomposing the time-delay interval into two nonequidistant subintervals to derive less conservative stability conditions. Then, by using Wirtinger-based inequality, reciprocally, and extended reciprocally convex combination lemmas, tight estimations for sum terms in the forward difference of the LKF are given. Several zero equalities are introduced to further relax the existing results. Less conservative stability criteria are proposed in terms of linear matrix inequalities (LMIs). Finally, numerical examples are proposed to show the effectiveness and less conservativeness of the proposed method.
引用
收藏
页数：15
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