论文介绍了基于核空间的ICA的原理和基本算法，然后介绍了该算法与典型ICA和主成分分析(PCA)在盲源信号分离中的比较。

In this paper, kernel independent component analysis (KICA) 's principle and algorithm are introduced, and then the KICA comparison with some other ICA and principal component analysis (PCA) is given.

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基于OR L人脸库，识别核主成分分析提取出的主成分的相关性系数。

Based on ORL face database, recognizes correlation coefficients of principal component extracted by KPCA.

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本文的主要工作是将支持向量机(SVM)及核主成分分析(KPCA)应用到入侵检测技术中。

The dissertation mainly aims at applying support vector machine (SVM) and kernel principal component analysis (KPCA) to intrusion detection.

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本文的主要工作是将支持向量机(SVM)及核主成分分析(KPCA)应用到入侵检测技术中。

The dissertation mainly aims at applying support vector machine (SVM) and kernel principal component analysis (KPCA) to intrusion detection.

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