计算机工程与应用2012，Vol.48Issue(9)：108-110,119,4.DOI:10.3778/j.issn.1002-8331.2012.09.032
基于K-EROS的QAR数据集的相似性分析
Similarity analysis of QAR data sets based on K-EROS
摘要
Abstract
This paper analyzes the problems of traditional Principal Component Analysis (PCA) when comparing the similarity of QAR data. The Kernel Principal Component Analysis(KPCA) based on EROS is proposed to deal with these problems. This paper introduces EROS method without vector treatment and adopts the kernel matrix of principal component analysis to reduce the dimension of QAR data. This paper gives classification on two groups of QAR data sets by using support vector products method with selecting different number of principal component, and compares it with SPCA and GPCA method. The results show that the proposed method used for QAR data has a good effect on classification.关键词
快速存取记录器(QAR)数据/主成分分析/核矩阵/相似性Key words
Quick Access Recorder(QAR) data/ Principal Component Analysis/ kernel matrix/ similarity分类
信息技术与安全科学引用本文复制引用
冯小荣,冯兴杰,冯增才..基于K-EROS的QAR数据集的相似性分析[J].计算机工程与应用,2012,48(9):108-110,119,4.基金项目
国家自然科学基金(No.60672174,60776806). （No.60672174,60776806）
