DOI码：10.1109/TNNLS.2015.2490168
所属单位：Guangdong University of Technology
教研室：Guangdong Key Lab. of Inter. of Things Info. Proc.
发表刊物：IEEE Transactions on Neural Networks and Learning
刊物所在地：IEEE/IEE Electronic Library
项目来源：National Natural Science Foundation of China, Grants: 61320106009, 61320106010, 61503106
关键字：coupled Markovian neural networks, sensor nonlinearity, state estimation, stochastic finite-time
摘要：This paper investigates the issue of finite-time state estimation for coupled Markovian neural networks subject to sensor nonlinearities, where the Markov chain with partially unknown transition probabilities is considered. A Luenberger type state estimator is proposed based on incomplete measurements, and the estimation error system is derived by using the Kronecker product. By using the Lyapunov method, sufficient conditions are established, which guarantee that the estimation error system is stochastically finite-time bounded and stochastically finite-time stable, respectively.
合写作者：Hui Peng,Renquan Lu, Yong Xu
第一作者：王卓
论文类型：基础研究
文献类型：期刊
卷号：28
期号：3
页面范围：630--638
是否译文：否
发表时间：2017-03-15
收录刊物：SCI、EI