FIR systems identification under quantized output observations and a large class of persistently exciting quantized inputs
文献类型：期刊论文
| 作者 | He, Yanyu1; Guo, Jin2 |
| 刊名 | JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
 |
| 出版日期 | 2017-10-01 |
| 卷号 | 30期号:5页码:1061-1071 |
| 关键词 | Asymptotic efficiency FIR system identification quantized input quantized output observations |
| ISSN号 | 1009-6124 |
| DOI | 10.1007/s11424-017-5305-7 |
| 英文摘要 | This paper investigates the FIR systems identification with quantized output observations and a large class of quantized inputs. The limit inferior of the regressors' frequencies of occurrences is employed to characterize the input's persistent excitation, under which the strong convergence and the convergence rate of the two-step estimation algorithm are given. As for the asymptotical efficiency, with a suitable selection of the weighting matrix in the algorithm, even though the limit of the product of the Cram,r-Rao (CR) lower bound and the data length does not exist as the data length goes to infinity, the estimates still can be asymptotically efficient in the sense of CR lower bound. A numerical example is given to demonstrate the effectiveness and the asymptotic efficiency of the algorithm. |
| 资助项目 | National Natural Science Foundation of China[61174042] ; National Natural Science Foundation of China[61403027] ; National Key Research and Development Program of China[2016YFB0901902] ; SKLMCCS[20160105] |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000406359400005 |
| 出版者 | SPRINGER HEIDELBERG |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/26173]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Guo, Jin |
| 作者单位 | 1.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China 2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China |
| 推荐引用方式 GB/T 7714 | He, Yanyu,Guo, Jin. FIR systems identification under quantized output observations and a large class of persistently exciting quantized inputs[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2017,30(5):1061-1071. |
| APA | He, Yanyu,&Guo, Jin.(2017).FIR systems identification under quantized output observations and a large class of persistently exciting quantized inputs.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,30(5),1061-1071. |
| MLA | He, Yanyu,et al."FIR systems identification under quantized output observations and a large class of persistently exciting quantized inputs".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY 30.5(2017):1061-1071. |
入库方式： OAI收割
来源：数学与系统科学研究院
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