自组织拓扑映射与主曲线学习

计算机科学 ›› 2006, Vol. 33 ›› Issue (3): 151-154.

自组织拓扑映射与主曲线学习

倪劲松李玉珍王宜怀

苏州大学数学科学学院,苏州215006 苏州大学计算机科学与技术学院,苏州215006

出版日期:2018-11-17 发布日期:2018-11-17
基金资助:
江苏省教育厅自然科学基金资助项目（02KJD52001）.

NI Jin-Song　, LI Yu-Zheng,　 WANG Yi-Huai　（Mathematics and Information Science College, Suzhou University, Suzhou 215006 ）

Online:2018-11-17 Published:2018-11-17

摘要/Abstract

摘要： 本文利用自组织拓扑映射方法设计了一种简易主曲线学习的算法，该算法继承了HS主曲线算法和K主曲线算法的主要优点，同时降低了一般主曲线算法的难度，使其变得更简洁明了.

关键词: 向量量化器自组织拓扑映射 Voronoi邻域主曲线

Abstract: We use the method of self-organized topological mapping to design a learning algorithm of principal curves. The algorithm is composed by two parts. In the first part, based on the theory of generalized vector guantizer, we have achieved refined GL-algorit

Key words: Vector quantizer, Self-organized topologicai mapping, Voronoi neighborhood, Principle curve

倪劲松李玉珍王宜怀. 自组织拓扑映射与主曲线学习[J]. 计算机科学, 2006, 33(3): 151-154. https://doi.org/

NI Jin-Song　, LI Yu-Zheng,　 WANG Yi-Huai　（Mathematics and Information Science College, Suzhou University, Suzhou 215006 ）. [J]. Computer Science, 2006, 33(3): 151-154. https://doi.org/

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