动态SVDD算法及其应用  

Dynamic SVDD Algorithm and its Application

作　　者：彭敏晶[1,2] 肖健华[1] 

机构地区：[1]五邑大学系统科学与技术研究所,江门529020 [2]华南理工大学工商管理学院,广州510641

出　　处：《计算机科学》2009年第3期156-157,183,共3页Computer Science

基　　金：中国博士后科学基金资助项目(2005038042);广东省科技计划项目(2006B12701002)资助

摘　　要：针对当前SVDD算法由于过大的优化规模导致检测计算时间过长的问题,提出了动态SVDD算法。通过分析在进行检测工作时新加入检测对象对正域边界的影响,提出:采用核方法形成的边界可近似替代折线所形成的边界。这样,加入新检测对象后,新的边界就只与新的样本点和之前的边界有关,从而可以大大减小优化规模,提高检测的效率。In order to solve the problem of long computation time in detecting caused by over-large optimization scale in SVDD,a dynamic support vector data description was proposed. After analyzing a new object＇ s influence on positive border,it was suggested that the boundary formed by kernel methods could be approximately replaced by boundary formed by polygonal lines. Thus, after adding new objects, the corresponding new boundary was only related with new objects and previous boundary, which means the optimization scale was largely decreased and the efficiency of detecting was promoted.

关 键 词：SVDD 边界 支持向量 核方法 优化规模 

分 类 号：TP331.1[自动化与计算机技术—计算机系统结构] TN911.7[自动化与计算机技术—计算机科学与技术]