A delay-decomposition approach for stability of neural network with time-varying delay

doi:10.1088/1674-1056/18/12/017

中国物理B ›› 2009, Vol. 18 ›› Issue (12): 5203-5211.doi: 10.1088/1674-1056/18/12/017

A delay-decomposition approach for stability of neural network with time-varying delay

崔宝同¹, 籍艳¹, 邱芳²

(1)College of Communications and Control Engineering, Jiangnan University, Wuxi 214122, China; (2)College of Communications and Control Engineering, Jiangnan University, Wuxi 214122, China;Department of Mathematics, Binzhou University, Binzhou 256603, China

收稿日期:2009-04-01 修回日期:2009-05-19 出版日期:2009-12-20 发布日期:2009-12-20
基金资助:
Project supported by the National Natural Science Foundation of China (Grant No 60674026) and the Natural Science Foundation of Jiangsu Province of China (Grant No BK2007016).

A delay-decomposition approach for stability of neural network with time-varying delay

Qiu Fang(邱芳)^a)b)^†, Cui Bao-Tong (崔宝同)^a), and Ji Yan(籍艳)^a)

^a College of Communications and Control Engineering, Jiangnan University, Wuxi 214122, China; ^b Department of Mathematics, Binzhou University, Binzhou 256603, China

Received:2009-04-01 Revised:2009-05-19 Online:2009-12-20 Published:2009-12-20
Supported by:
Project supported by the National Natural Science Foundation of China (Grant No 60674026) and the Natural Science Foundation of Jiangsu Province of China (Grant No BK2007016).

摘要/Abstract

摘要： This paper studies delay-dependent asymptotical stability problems for the neural system with time-varying delay. By dividing the whole interval into multiple segments such that each segment has a different Lyapunov matrix, some improved delay-dependent stability conditions are derived by employing an integral equality technique. A numerical example is given to demonstrate the effectiveness and less conservativeness of the proposed methods.

Abstract: This paper studies delay-dependent asymptotical stability problems for the neural system with time-varying delay. By dividing the whole interval into multiple segments such that each segment has a different Lyapunov matrix, some improved delay-dependent stability conditions are derived by employing an integral equality technique. A numerical example is given to demonstrate the effectiveness and less conservativeness of the proposed methods.

Key words: neural system, global asymptotical stability, time-varying delay

中图分类号: (Neural networks, fuzzy logic, artificial intelligence)

07.05.Mh

02.10.Yn (Matrix theory)

邱芳, 崔宝同, 籍艳. A delay-decomposition approach for stability of neural network with time-varying delay[J]. 中国物理B, 2009, 18(12): 5203-5211.

Qiu Fang(邱芳), Cui Bao-Tong (崔宝同), and Ji Yan(籍艳). A delay-decomposition approach for stability of neural network with time-varying delay[J]. Chin. Phys. B, 2009, 18(12): 5203-5211.

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A delay-decomposition approach for stability of neural network with time-varying delay

A delay-decomposition approach for stability of neural network with time-varying delay

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