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Asymptotically efficient identification of FIR systems with quantized observations and general quantized inputs

文献类型：期刊论文

作者Guo, Jin1; Wang, Le Yi2; Yin, George3; Zhao, Yanlong4; Zhang, Ji-Feng4
刊名AUTOMATICA
出版日期2015-07-01
卷号57页码:113-122
关键词System identification Quantization Non-periodic input Asymptotic efficiency Input design
ISSN号0005-1098
DOI10.1016/j.automatica.2015.04.009
英文摘要This 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.
资助项目Army 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研究方向Automation & Control Systems ; Engineering
语种英语
WOS记录号WOS:000356746500015
出版者PERGAMON-ELSEVIER SCIENCE LTD
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/20097]  
专题系统科学研究所
通讯作者Guo, Jin
作者单位1.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
推荐引用方式
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.

入库方式： OAI收割

来源：数学与系统科学研究院

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