iterativeparameterestimatewithbatchedbinaryvaluedobservations

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	iterativeparameterestimatewithbatchedbinaryvaluedobservations
	Zhao Yanlong; Bi Wenjian; Wang Ting
	2016
发表期刊	sciencechinainformationsciences
ISSN	1674-733X
卷号	59 期号:5 页码:18
摘要	Abstract In this paper, we consider linear system identification with batched binary-valued observations. We constructed an iterative parameter estimate algorithm to achieve the maximum likelihood (ML) estimate. The first interesting result was that there exists at most one finite ML solution for this specific maximum likelihood problem, which was induced by the fact that the Hessian matrix of the log-likelihood function was negative definite under binary data and Gaussian system noises. The global concave property and local strongly concave property of the log-likelihood function were obtained. Under mild conditions on the system input, we proved that the ML function has a unique maximum point. The second main result was that the ML estimate was consistent under persistent excitation inputs, which infers the effectiveness of ML estimate. Finally, the proposed iterative estimate algorithm converged to a fixed vector with an exponential rate that was proved by constructing a Lyapunov function. A more interesting result was that the limit of the iterative algorithm achieved the maximization of the ML function. Numerical simulations are illustrated to support the theoretical results obtained in this paper well.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/47322
专题	系统科学研究所
作者单位	中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Zhao Yanlong,Bi Wenjian,Wang Ting. iterativeparameterestimatewithbatchedbinaryvaluedobservations[J]. sciencechinainformationsciences,2016,59(5):18.
APA	Zhao Yanlong,Bi Wenjian,&Wang Ting.(2016).iterativeparameterestimatewithbatchedbinaryvaluedobservations.sciencechinainformationsciences,59(5),18.
MLA	Zhao Yanlong,et al."iterativeparameterestimatewithbatchedbinaryvaluedobservations".sciencechinainformationsciences 59.5(2016):18.