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In the literature of astronomical spectral classification, linear principle component analysis (PCA) was frequently employed to extract features of spectra data. However, the spectral data are too complicated to be well described by a linear model. In this paper, kernel independent component analysis (KICA), which contains a nonlinear kernel mapping component, is adopted to extract features from the...
The truth about what chemicals are to be found on the surface of Mars lies hidden in Gigabytes of hyperspectral data. How to reveal this mystery is the subject of this paper. Independent component analysis (ICA) is used for identification and classification of endmembers and for artifact removal. The classification results are compared with the result of a wavelet classifier and reference spectra...
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