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identificationofthegainsystemwithquantizedobservationsandboundedpersistentexcitations
Guo Jin; Zhao Yanlong
2014
Source Publicationsciencechinainformationscience
ISSN1674-733X
Volume57Issue:1
AbstractSystem 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.
Language英语
Funding Project[National Natural Science Foundation of China] ; [Youth Innovation Promotion Association of Chinese Academy of Sciences]
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/50196
Collection系统科学研究所
Affiliation中国科学院数学与系统科学研究院
Recommended Citation
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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