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Map PDF

5 Pages·2019·English
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by ['Marc Asenjo']| 2019| 5 pages| English

About Map

This document discusses applying principal component analysis (PCA) to spectral data from the Sloan Digital Sky Survey (SDSS) database to classify stars. 300 spectra of each spectral type were obtained from SDSS and compiled into a data matrix. PCA was then used to analyze the data matrix to identify correlations between spectral types without altering the original information. The eigenvalues and eigenvectors resulting from PCA represent the principal components that account for variance in the data and can be used for spectral classification.

Detailed Information

Author:['Marc Asenjo']
Publication Year:2019
Pages:5
Language:English
Format:PDF
Price:FREE
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