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 :
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