Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays

This paper investigates the problem of dependent stability criteria for neutral type neural networks with mixed time-varying delays. Firstly, some new delay-dependent stability results are obtained by employing the more general partitioning approach and generalizing the famous Jensen inequality. Sec...

Full description

Bibliographic Details
Main Authors:	Kaibo Shi, Hong Zhu, Shouming Zhong, Yong Zeng, Yuping Zhang, Li Liang
Format:	Article
Language:	English
Published:	Hindawi Limited 2013-01-01
Series:	Journal of Applied Mathematics
Online Access:	http://dx.doi.org/10.1155/2013/450175

id	doaj-d2c45dd687b849a2bb9978a837fd2e26
record_format	Article
spelling	doaj-d2c45dd687b849a2bb9978a837fd2e262020-11-24T23:52:20ZengHindawi LimitedJournal of Applied Mathematics1110-757X1687-00422013-01-01201310.1155/2013/450175450175Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying DelaysKaibo Shi0Hong Zhu1Shouming Zhong2Yong Zeng3Yuping Zhang4Li Liang5School of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaSchool of Automation Engineering, University of Electronic Science and Technology of China, Chengdu 611731, ChinaCollege of Information Sciences and Technology, Hainan University, Haikou 570228, ChinaThis paper investigates the problem of dependent stability criteria for neutral type neural networks with mixed time-varying delays. Firstly, some new delay-dependent stability results are obtained by employing the more general partitioning approach and generalizing the famous Jensen inequality. Secondly, based on a new type of Lyapunov-Krasovskii functional with the cross terms of variables, less conservative stability criteria are proposed in terms of linear matrix inequalities (LMIs). Furthermore, it is the first time that the idea of second-order convex combination and the property of quadratic convex function applied to the derivation of neutral type neural networks play an important role in reducing the conservatism of the paper. Finally, four numerical examples are given to show the effectiveness and the advantage of the proposed method.http://dx.doi.org/10.1155/2013/450175
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Kaibo Shi Hong Zhu Shouming Zhong Yong Zeng Yuping Zhang Li Liang
spellingShingle	Kaibo Shi Hong Zhu Shouming Zhong Yong Zeng Yuping Zhang Li Liang Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays Journal of Applied Mathematics
author_facet	Kaibo Shi Hong Zhu Shouming Zhong Yong Zeng Yuping Zhang Li Liang
author_sort	Kaibo Shi
title	Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays
title_short	Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays
title_full	Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays
title_fullStr	Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays
title_full_unstemmed	Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays
title_sort	less conservative stability criteria for neutral type neural networks with mixed time-varying delays
publisher	Hindawi Limited
series	Journal of Applied Mathematics
issn	1110-757X 1687-0042
publishDate	2013-01-01
description	This paper investigates the problem of dependent stability criteria for neutral type neural networks with mixed time-varying delays. Firstly, some new delay-dependent stability results are obtained by employing the more general partitioning approach and generalizing the famous Jensen inequality. Secondly, based on a new type of Lyapunov-Krasovskii functional with the cross terms of variables, less conservative stability criteria are proposed in terms of linear matrix inequalities (LMIs). Furthermore, it is the first time that the idea of second-order convex combination and the property of quadratic convex function applied to the derivation of neutral type neural networks play an important role in reducing the conservatism of the paper. Finally, four numerical examples are given to show the effectiveness and the advantage of the proposed method.
url	http://dx.doi.org/10.1155/2013/450175
work_keys_str_mv	AT kaiboshi lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays AT hongzhu lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays AT shoumingzhong lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays AT yongzeng lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays AT yupingzhang lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays AT liliang lessconservativestabilitycriteriaforneutraltypeneuralnetworkswithmixedtimevaryingdelays
_version_	1725473616689102848

Less Conservative Stability Criteria for Neutral Type Neural Networks with Mixed Time-Varying Delays

Similar Items