Nonlinear compressed measurement identification based on Volterra series

doi:10.11887/j.cn.202001017

NSSC OpenIR

	Nonlinear compressed measurement identification based on Volterra series
Alternative Title	20200808196873;Volterra 级数模型的非线性压缩测量辨识算法
	Qiu, Peng 1,2; Yao, Xuri 1; Li, Mingqian 1,2; Zhai, Guangjie 1
Source Publication	Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology
	2020
Volume	42 Issue:1 Pages:125-132
DOI	10.11887/j.cn.202001017
ISSN	10012486
Language	中文
Keyword	Compressed sensing - Identification (control systems) - Nonlinear systems - Religious buildings Identification algorithms - Identification problem - Least square methods - Measurement matrix - Multiple measurements - Nonlinear compression - Orthogonal matching pursuit - Volterra Series
Abstract	For the identification problem of nonlinear systems, the accuracy and stability of the nonlinear compression measurement identification algorithm were proved in the simulation experiment, and the complete signal was obtained accurately only by using constant multiple measurement times of the signal sparsity. Compared with the least square method, the proposed algorithm has greatly reduced the needed measurements, therefore, it is possible for the identification of high-order Volterra series. Furthermore, the influence of all factors on the accuracy of system identification was analyzed, such as signal sparsity, measurement noise, measurement matrix form, etc. © 2020, NUDT Press. All right reserved.
Indexed By	EI ; CSCD
Citation statistics
Document Type	期刊论文
Identifier	http://ir.nssc.ac.cn/handle/122/7494
Collection	中国科学院国家空间科学中心
Affiliation	1.National Space Science Center, Chinese Academy of Sciences, Beijing; 100190, China; 2.University of Chinese Academy of Sciences, Beijing; 100049, China
Recommended Citation GB/T 7714	Qiu, Peng,Yao, Xuri,Li, Mingqian,et al. Nonlinear compressed measurement identification based on Volterra series[J]. Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology,2020,42(1):125-132.
APA	Qiu, Peng,Yao, Xuri,Li, Mingqian,&Zhai, Guangjie.(2020).Nonlinear compressed measurement identification based on Volterra series.Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology,42(1),125-132.
MLA	Qiu, Peng,et al."Nonlinear compressed measurement identification based on Volterra series".Guofang Keji Daxue Xuebao/Journal of National University of Defense Technology 42.1(2020):125-132.

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