LS-Based Parameter Estimation of DARMA Systems with Uniformly Quantized Observations
文献类型：期刊论文
| 作者 | Jing Lida; Zhang Ji-Feng2 |
| 刊名 | JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
 |
| 出版日期 | 2021-08-08 |
| 页码 | 18 |
| 关键词 | Discrete-time linear time-invariant systems parameter estimation quantized output |
| ISSN号 | 1009-6124 |
| DOI | 10.1007/s11424-021-0314-y |
| 英文摘要 | This paper is concerned with the parameter estimation of deterministic autoregressive moving average (DARMA) systems with quantization data. The estimation algorithms adopted here are the least squares (LS) and the forgetting factor LS, and the signal quantizer is of uniform, that is, with uniform quantization error. The authors analyse the properties of the LS and the forgetting factor LS, and establish the boundedness of the estimation errors and a relationship of the estimation errors with the size of quantization error, which implies that the smaller the quantization error is, the smaller the estimation error is. A numerical example is given to demonstrate theorems. |
| 资助项目 | National Key R&D Program of China[2018YFA0703800] ; National Natural Science Foundation of China[61877057] |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000682818700003 |
| 出版者 | SPRINGER HEIDELBERG |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/59044]  |
| 专题 | 中国科学院数学与系统科学研究院 |
| 通讯作者 | Zhang Ji-Feng |
| 作者单位 | 1.Univ Chinese Acad Sci, Sch Math Sci, Beijing 100049, Peoples R China 2.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 | Jing Lida,Zhang Ji-Feng. LS-Based Parameter Estimation of DARMA Systems with Uniformly Quantized Observations[J]. JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,2021:18. |
| APA | Jing Lida,&Zhang Ji-Feng.(2021).LS-Based Parameter Estimation of DARMA Systems with Uniformly Quantized Observations.JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY,18. |
| MLA | Jing Lida,et al."LS-Based Parameter Estimation of DARMA Systems with Uniformly Quantized Observations".JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY (2021):18. |
入库方式： OAI收割
来源：数学与系统科学研究院
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