DocumentCode
3660873
Title
An approach for space registration based on support vector machine
Author
Zhuyun Niu; Chaowei Chang; Teng Li
Author_Institution
North Automatic Control Technology Institute, ShanXi, TaiYuan, 030006, China
fYear
2015
Firstpage
135
Lastpage
140
Abstract
The characteristic and applicability of nonparametric estimation are studied in this paper. A method of space registration based on support vector machine (SVM) is proposed. It is compared with the method of sensor registration based on neural network and the method of generalized least square estimator (GLS) in multi-kind parameters. The results illustrate that the method of space registration based on support vector machine is effective.
Keywords
"Chaos","Training"
Publisher
ieee
Conference_Titel
Estimation, Detection and Information Fusion (ICEDIF), 2015 International Conference on
Type
conf
DOI
10.1109/ICEDIF.2015.7280177
Filename
7280177
Link To Document