MOBILE GEO-LOCATION ALGORITHM BASED ON LS-SVM

被引：1
|
作者：
Sun Guolin Guo Wei (Institute of Communication and Information Engineering
机构：
来源：
Journal of Electronics(China) | 2005年 / 04期
关键词：
Mobile geo-location; Least Squares Support Vector Machines (LS-SVM); Machine learning;
D O I：
暂无
中图分类号：
TN929.5 [移动通信];
学科分类号：
080402 ; 080904 ; 0810 ; 081001 ;
摘要：
Support Vector Machine (SVM) is a powerful methodology for solving problems in non-linear classification, function estimation and density estimation, which has also led to many other recent developments in kernel based methods in general. This paper presents a high accuracy and fault-tolerant SVM for the mobile geo-location problem, which is an important component of pervasive computing. Simulation results show its basic location performance, and illustrate impacts of the number of training samples and training area on test location error.
引用
收藏
页码：351 / 356
页数：6
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