Combining SOM and local minimum enclosing spheres for novelty detection

摘要：

In this paper, a novelty detection method based on self-organizing map (SOM) and local minimum enclosing spheres is proposed. There are two phases in the proposed approach. In the first phase, the whole training set are split into disjointed Voronoi regions by SOM. In the second phase, several local minimum enclosing spheres are constructed upon these Voronoi regions. Compared with its related works, the proposed method demonstrates better performances on one synthetic data set and two benchmark data sets.

关键词： Self-Organizing Map Local Minimum Enclosing Spheres Novelty Detection

作者: Hong-Jie Xing Ming-Hu Ha Xi-Zhao Wang

作者单位: College of Mathematics and Computer Science, Hebei University, Baoding, Hebei Province, China

会议类型: 国际会议

会议名称: 2009年中国控制与决策会议(2009 Chinese Control and Decision Conference)

会议地点: 广西桂林

会议语种:英文

页码: 3771-3776

在线出版日期: 2009-06-17（万方平台首次上网日期，不代表论文的发表时间）