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	Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays
	Wang, Zidong1,2; Liu, Yurong3; Liu, Xiaohui2; Shi, Yong4
刊名	Neurocomputing
	2010-12-01
卷号	74期号:1-3页码:256-264
关键词	Stochastic neural networks Robust estimation Probabilistic measurement delays Time varying delays Stochastic disturbances Lyapunov-krasovskii functional
ISSN号	0925-2312
通讯作者	Wang, zidong()
英文摘要	In this paper the robust h-infinity state estimation problem is investigated for a general class of uncertain discrete-time stochastic neural networks with probabilistic measurement delays the measurement delays of the neural networks are described by a binary switching sequence satisfying a conditional probability distribution the neural network under study involves parameter uncertainties stochastic disturbances and time-varying delays and the activation functions are characterized by sector-like nonlinearities the problem addressed is the design of a full-order state estimator for all admissible uncertainties nonlinearities and time-delays the dynamics of the estimation error is constrained to be robustly exponentially stable in the mean square and at the same time a prescribed h-infinity disturbance rejection attenuation level is guaranteed by using the lyapunov stability theory and stochastic analysis techniques sufficient conditions are first established to ensure the existence of the desired estimators these conditions are dependent on the lower and upper bounds of the time-varying delays then the explicit expression of the desired estimator gains is described in terms of the solution to a linear matrix inequality (lmi) finally a numerical example is exploited to show the usefulness of the results derived (c) 2010 elsevier b v all rights reserved
WOS关键词	GLOBAL ASYMPTOTIC STABILITY ; EXPONENTIAL STABILITY ; DISTRIBUTED DELAYS ; H-INFINITY ; SECTOR NONLINEARITIES ; VARYING DELAYS ; SYSTEMS ; SYNCHRONIZATION
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000285805800023
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/2414262
专题	中国科学院大学
通讯作者	Wang, Zidong
作者单位	1.Donghua Univ, Sch Informat Sci & Technol, Shanghai 200051, Peoples R China 2.Brunel Univ, Dept Informat Syst & Comp, Uxbridge UB8 3PH, Middx, England 3.Yangzhou Univ, Dept Math, Yangzhou 225002, Peoples R China 4.Chinese Acad Sci, CAS Res Ctr Fictitious Econ & Data Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Wang, Zidong,Liu, Yurong,Liu, Xiaohui,et al. Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays[J]. Neurocomputing,2010,74(1-3):256-264.
APA	Wang, Zidong,Liu, Yurong,Liu, Xiaohui,&Shi, Yong.(2010).Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays.Neurocomputing,74(1-3),256-264.
MLA	Wang, Zidong,et al."Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays".Neurocomputing 74.1-3(2010):256-264.

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