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 highaccuracy 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.

原文链接:http://www.cqvip.com//QK/85266X/200504/16076024.html

送人玫瑰，手留余香~如您已下载到该资源，可在回帖当中上传与大家共享，欢迎来CDA社区交流学习。（仅供学术交流用。）