An Approach for Space Registration Based on Support Vector Machine

被引：0
|
作者：
Niu, Zhuyun [1 ]
Chang, Chaowei [1 ]
Li, Teng [1 ]
机构：
[1] North Automat Control Technol Inst, Taiyuan 030006, Shanxi, Peoples R China
来源：
PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON ESTIMATION, DETECTION AND INFORMATION FUSION ICEDIF 2015 | 2015年
关键词：
nonparametric estimation; space registration; support vector machine; neural network;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
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.
引用
收藏
页码：135 / 140
页数：6
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