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动态SVDD算法及其应用

Dynamic SVDD Algorithm and its Application

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【作者】 彭敏晶肖健华

【Author】 PENG Min-jing1,2 XIAO Jian-hua1 (Systems Science and Technology Institute,Wuyi University,Jiangmen 529020,China)1(School of Business Administration,South China University of Technology,Guangzhou 510641,China)2

【机构】 五邑大学系统科学与技术研究所华南理工大学工商管理学院

【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。

【Abstract】 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
【Key words】 SVDDBoundarySupport vectorKernel methodsOptimization scale
【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
  • 【文献出处】 计算机科学 ,Computer Science , 编辑部邮箱 ,2009年03期
  • 【分类号】TP301.6
  • 【被引频次】6
  • 【下载频次】273
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