Novel delay-dependent stability criteria for neural networks with interval time-varying delay

doi:10.1088/1674-1056/20/12/120701

Abstract The problem of delay-dependent asymptotic stability for neural networks with interval time-varying delay is investigated. Based on the idea of delay decomposition method, a new type of Lyapunov-Krasovskii functional is constructed. Several novel delay-dependent stability criteria are presented in terms of linear matrix inequality by using the Jensen integral inequality and a new convex combination technique. Numerical examples are given to demonstrate that the proposed method is effective and less conservative.

Keywords: neural networks interval time-varying delay delay-dependent stability convex combination linear matrix inequality

Received: 20 March 2011
Revised: 10 July 2011
Accepted manuscript online:

PACS:	07.05.Mh	(Neural networks, fuzzy logic, artificial intelligence)
	02.10.Yn	(Matrix theory)
	02.30.Yy	(Control theory)

Fund: Project supported by the Doctoral Startup Foundation of Taiyuan University of Science and Technology, China (Grant No. 20112010).

Cite this article:

Wang Jian-An(王健安) Novel delay-dependent stability criteria for neural networks with interval time-varying delay 2011 Chin. Phys. B 20 120701

[1]	van Putten M and Stam C J 2001 Phys. Lett. A 281 131
[2]	Arik S 2004 Neural Netw. 17 1027
[3]	Chen T and Rong L 2003 Phys. Lett. A 317 436
[4]	Cao J D and Wang L 2002 IEEE Trans. Neural Netw. 13 457
[5]	Singh V 2004 IEEE Trans. Neural Netw. 15 223
[6]	Cui B T, Chen J and Lou X Y 2008 Chin. Phys. B 17 1670
[7]	Chen Y G and Wu Y Y 2009 Neurocomputing 72 1065
[8]	Chen D L and Zhang W D 2008 Chin. Phys. B 17 1506
[9]	Lee S M, Kwon O M and Park J H 2010 Chin. Phys. B 19 050507
[10]	Sun J, Liu G P, Chen J and Rees D 2009 Phys. Lett. A 373 342
[11]	Hua C C, Long C N and Guan X P 2006 Phys. Lett. A 352 335
[12]	Xu S Y, Lam J and Ho D W C 2008 Int. J. Bifur. Chaos 18 245
[13]	He Y, Wu M and She J H 2006 IEEE Trans. Circuits Syst. II 53 553
[14]	He Y, Liu G P and Rees D 2007 IEEE Trans. Neural Netw. 18 310
[15]	Shao H Y 2010 Circuits, Systems, and Signal Processing 29 637
[16]	Li T, Guo L, Sun C Y and Lin C 2008 IEEE Trans. Neural Netw. 19 726
[17]	Li T and Ye X L 2010 Neurocomputing 73 1038
[18]	Zheng C D, Zhang H G and Wang Z S 2009 IEEE Trans. Circuits Syst. II 56 605
[19]	Zheng C D, Zhang H G and Wang Z S 2010 IEEE Trans. Circuits Syst. II 57 41
[20]	Mou S S, Gao H J, Lam J and Qiang W Y 2008 IEEE Trans. Neural. Netw. 19 532
[21]	Xiao S P and Zhang X M 2009 IEEE Trans. Circuits Syst. II 56 659
[22]	Zhang X M and Han Q L 2009 IEEE Trans. Neural Netw. 20 533
[23]	Qiu F, Cui B T and Ji Y 2009 Chin. Phys. B 18 5203
[24]	Tian J K and Xie X J 2010 Phys. Lett. A 374 938
[25]	He Y, Liu G P, Rees D and Wu M 2007 IEEE Trans. Neural Netw. 18 1850
[26]	Tian J K and Zhou X B 2010 Expert System with Applications 37 7521
[27]	Chen J, Sun J, Liu G P and Rees D 2010 Phys. Lett. A 374 4397
[28]	Zuo Z Q, Yang C L and Wang Y J 2010 IEEE Trans. Neural Netw. 21 339
[29]	Gu K Q 2000 Proc. 39/th IEEE Conf. Decision and Control p. 2805
[30]	Zhu X L, Wang Y and Yang G H 2010 IET Control Theory Appl. 4 1101

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Novel delay-dependent stability criteria for neural networks with interval time-varying delay

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