%0 Journal Article
%T Learning algorithms for self organizing mapping based on partial distortion search<br>基于部分失真搜索的自组织映射学习算法
%A CHEN Zuo-ping
%A YE Zheng-lin
%A ZHAO Hong-xing
%A ZHENG Hong-chan
%A <br>陈作平
%A 叶正麟
%A 赵红星
%A 郑红婵
%J 计算机应用
%D 2006
%I 
%X To accelerate the learning process of Self-Organizing Mapping in the situation of large mount of data or high dimension, two learning algorithms were proposed in this paper, by using Partial Distortion Search and Extended Partial Distortion Search respectively to solve the problem of Nearest Neighbor Search during learning process, which could reduce the multiplications greatly. Experiment results indicate that the proposed algorithms can save up to 1/3 and 1/2 multiplications, compared with traditional Self-Organizing Mapping learning algorithm.
%K Self Organizing Map
%K partial distortion search
%K nearest neighbor search<br>自组织映射
%K 部分失真搜索
%K 最近邻搜索
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=54AE282E3B9728C2&yid=37904DC365DD7266&vid=96C778EE049EE47D&iid=0B39A22176CE99FB&sid=D98387EFB283C5E0&eid=CCA069A173D8C5B4&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=12