H_(∞) state estimation for Markov jump neural networks with transition probabilities subject to the persistent dwell-time switching rule  

作　　者：Hao Shen Jia-Cheng Wu Jian-Wei Xia Zhen Wang 沈浩;吴佳成;夏建伟;王震(College of Electrical and Information Engineering,Anhui University of Technology,Ma'anshan 243032,China;School of Mathematical Sciences,Liaocheng University,Liaocheng 252059,China;College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao 266590,China)

机构地区：[1]College of Electrical and Information Engineering,Anhui University of Technology,Ma'anshan 243032,China [2]School of Mathematical Sciences,Liaocheng University,Liaocheng 252059,China [3]College of Electrical Engineering and Automation,Shandong University of Science and Technology,Qingdao 266590,China

出　　处：《Chinese Physics B》2021年第6期88-95,共8页中国物理B（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant Nos. 61873002, 61703004, 61973199, 61573008, and 61973200)。

摘　　要：We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-time switching rule,as a more general switching rule, is adopted to describe this variation characteristic. Afterwards, based on the classical Lyapunov stability theory, a Lyapunov function is established, in which the information about the Markov jump feature of the system mode and the persistent dwell-time switching of the transition probabilities is considered simultaneously.Furthermore, via using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H_(∞) performance level, from which the specific form of the estimator can be obtained. Finally, the rationality and effectiveness of the obtained results are verified by a numerical example.

关 键 词：Markov jump neural networks persistent dwell-time switching rule H_(∞)state estimation meansquare exponential stability 

分 类 号：TP13[自动化与计算机技术—控制理论与控制工程] TP183[自动化与计算机技术—控制科学与工程]