New delay-dependent stability criteria for recurrent neural networks with time-varying delays

被引：50
|
作者：
Yang, Bin [1 ]
Wang, Rui [2 ]
Shi, Peng [3 ,4 ]
Dimirovski, Georgi M. [5 ,6 ]
机构：
[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
[2] Dalian Univ Technol, Sch Aeronaut & Astronaut, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China
[3] Harbin Engn Univ, Coll Automat, Harbin 150001, Peoples R China
[4] Victoria Univ, Coll Engn & Sci, Melbourne, Vic 8001, Australia
[5] Dogus Univ, Sch Engn, TR-34722 Istanbul, Turkey
[6] Univ St Cyril & Methudius, Sch FEIT, MK-1000 Skopje, Macedonia
来源：
NEUROCOMPUTING | 2015年 / 151卷
基金：
澳大利亚研究理事会; 中国国家自然科学基金;
关键词：
Recurrent neural networks; Stability; Lyapunov-Krasovskii functional; Time-varying delays; GLOBAL EXPONENTIAL STABILITY; ROBUST STABILITY; SYSTEMS;
D O I：
10.1016/j.neucom.2014.10.048
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This work is concerned with the delay-dependentstability problem for recurrent neural networks with time-varying delays. A new improved delay-dependent stability criterion expressed in terms of linear matrix inequalities is derived by constructing a dedicated Lyapunov-Krasovskii functional via utilizing Wirtinger inequality and convex combination approach. Moreover, a further improved delay-dependent stability criterion is established by means of a new partitioning method for bounding conditions on the activation function and certain new activation function conditions presented. Finally, the application of these novel results to an illustrative example from the literature has been investigated and their effectiveness is shown via comparison with the existing recent ones. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码：1414 / 1422
页数：9
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