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KPCA主要在图像去噪声方面有应用。此外还可以进行特征提取，降维使用.-KPCA major noise in the image to have the application. You can also feature extraction using dimension reduction.
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kpca原始程序和小波去噪部分，用于数据降维和特征提取比较实用-kpca part of the original program and wavelet denoising for data dimensionality reduction and feature extraction more practical
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KPCA程序，可用于数据降维，特征提取，用起来比较简单-KPCA procedure can be used for data dimensionality reduction, feature extraction, using relatively simple
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kernel PCA feature extraction
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Kernel Principal Conponent Analysis 特征提取-Kernel Principal Conponent Analysis feature extraction
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A new method for performing a nonlinear form of Principal
Component Analysis proposed. By the use of integral operator kernel
functions, one can eciently compute principal components in high{
dimensional feature spaces, related to input space
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主成分分析的一种改进算法，是一种非线性的特征提取方法。(An improved algorithm of principal component analysis is a nonlinear feature extraction method)
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