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identificationofthegainsystemwithquantizedobservationsandboundedpersistentexcitations
Guo Jin; Zhao Yanlong
2014
发表期刊sciencechinainformationscience
ISSN1674-733X
卷号57期号:1
摘要System identification with quantized observations and persistent excitations is a fundamental and difficult problem. As the first step, this paper takes the gain system for example to investigate the identification with quantized observations and bounded persistently exciting inputs. Firstly, the identification with single threshold quantization is considered. A projection recursive algorithm is proposed to estimate the unknown parameter. By use of the conditional expectation of quantized observations with respect to the estimates, the algorithm is shown to be both mean-square and almost surely convergent. The upper bound of the convergence rate is also obtained, which has the same order as the one of the optimal estimation in the case where the system output is exactly known. Secondly, for the multi-threshold quantization, the identification algorithm is similarly constructed and its asymptotic property is analyzed. Using a multi-linear transformation, the optimal scheme of quantization values and thresholds is given. A numerical example is simulated to demonstrate the effectiveness of the algorithms and the main results obtained.
语种英语
资助项目[National Natural Science Foundation of China] ; [Youth Innovation Promotion Association of Chinese Academy of Sciences]
文献类型期刊论文
条目标识符http://ir.amss.ac.cn/handle/2S8OKBNM/50196
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
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GB/T 7714
Guo Jin,Zhao Yanlong. identificationofthegainsystemwithquantizedobservationsandboundedpersistentexcitations[J]. sciencechinainformationscience,2014,57(1).
APA Guo Jin,&Zhao Yanlong.(2014).identificationofthegainsystemwithquantizedobservationsandboundedpersistentexcitations.sciencechinainformationscience,57(1).
MLA Guo Jin,et al."identificationofthegainsystemwithquantizedobservationsandboundedpersistentexcitations".sciencechinainformationscience 57.1(2014).
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