主分量分析和独立分量分析方法的比较研究

英文篇名：Research on comparison of principal component analysis with inde- pendent component analysis
中文刊名：石油物探
英文刊名：Geophysical Prospecting for Petroleum
作者：(亩心)晓宇 ; 刘洪
英文作者：Xi Xiaoyu and Lin Hong. Institute of Geology & Geophysics ; Chinese Academy of Sciences ; Beijing 100029 ; China
中文关键词：主分量分析 ; 独立分量分析 ; 高阶统计量 ; 二阶统计量 ; 非高斯性
英文关键词：principal component analysis (PCA) ; independent component analysis (ICA) ; higher order statistics (HOS) ; second order statistics (SOS) ; nongaussianity
出版日期：2006-09-25
机构：中国科学院地质与地球物理研究所,中国科学院地质与地球物理研究所北京 100029,北京 100029
年：2006
期：05
出版单位：石油物探

摘要

统计特征方法在信号处理、模式识别等领域的应用越来越广泛,特别是独立分量分析(ICA)在理论研究和实际应用中备受关注。主分量分析(PCA)和独立分量分析总的方法和思路比较相似。在分析PCA和ICA的原理及特点的基础上,分别用PCA和ICA对模型和实际地震数据进行了验证,并比较和分析了两者在信号处理中的特征提取能力。结果表明:在实现信号分离时,PCA分解后的各个分量仍然保持一定的相关性,而ICA分解后的各个分量保持独立。
In recent years, statistical property methods have been applied extensively in signal processing and pattern recognition, with the independent component analysis (ICA) in particular because it has been improved in both theoretical research and actual application. The application of principal component analysis (PCA) and ICA are similar in signal processing. The principles and characteristics of PCA and ICA, PCA are analyzed and verified by theoretical model and real seismic data respectively. In addition, the extraction abilities of both methods in signal processing are compared and analyzed ; the result indicates that the PCA components are still related to each other while the ICA components keep independent.

引文

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