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Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs
Guo, Jin1; Wang, Le Yi2; Yin, George3; Zhao, Yanlong4; Zhang, Ji-Feng4
2015-07-01
Source PublicationAUTOMATICA
ISSN0005-1098
Volume57Pages:113-122
AbstractThis paper introduces identification algorithms for finite impulse response systems under quantized output observations and general quantized inputs. While asymptotically efficient algorithms for quantized identification under periodic inputs are available, their counterpart under general inputs has encountered technical difficulties and evaded satisfactory resolutions. Under quantized inputs, this paper resolves this issue with constructive solutions. A two-step algorithm is developed, which demonstrates desired convergence properties including strong convergence, mean-square convergence, convergence rates, asymptotic normality, and asymptotical efficiency in terms of the Cramer-Rao lower bound. Some essential conditions on input excitation are derived that ensure identifiability and convergence. It is shown that by a suitable selection of the algorithm's weighting matrix, the estimates become asymptotically efficient. The strong and mean-square convergence rates are obtained. Optimal input design is given. Also the joint identification of noise distribution functions and system parameters is investigated. Numerical examples are included to illustrate the main results of this paper. (C) 2015 Elsevier Ltd. All rights reserved.
KeywordSystem identification Quantization Non-periodic input Asymptotic efficiency Input design
DOI10.1016/j.automatica.2015.04.009
Language英语
Funding ProjectArmy Research Office[W911NF-12-1-0223] ; National Natural Science Foundation of China[61174042] ; National Natural Science Foundation of China[61403027] ; National Natural Science Foundation of China[612279002]
WOS Research AreaAutomation & Control Systems ; Engineering
WOS SubjectAutomation & Control Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000356746500015
PublisherPERGAMON-ELSEVIER SCIENCE LTD
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/20098
Collection系统科学研究所
Corresponding AuthorGuo, Jin
Affiliation1.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
2.Wayne State Univ, Dept Elect & Comp Engn, Detroit, MI 48202 USA
3.Wayne State Univ, Dept Math, Detroit, MI 48202 USA
4.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China
Recommended Citation
GB/T 7714
Guo, Jin,Wang, Le Yi,Yin, George,et al. Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs[J]. AUTOMATICA,2015,57:113-122.
APA Guo, Jin,Wang, Le Yi,Yin, George,Zhao, Yanlong,&Zhang, Ji-Feng.(2015).Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs.AUTOMATICA,57,113-122.
MLA Guo, Jin,et al."Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs".AUTOMATICA 57(2015):113-122.
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