Robust state estimation for discrete-time stochastic neural networks with probabilistic measurement delays
文献类型：期刊论文
| 作者 | Wang, Zidong1,2; Liu, Yurong3; Liu, Xiaohui2; Shi, Yong4 |
| 刊名 | Neurocomputing
 |
| 出版日期 | 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 |
| WOS记录号 | WOS:000285805800023 |
| 出版者 | ELSEVIER SCIENCE BV |
| URI标识 | http://www.irgrid.ac.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. |
入库方式： iSwitch采集
来源：中国科学院大学
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