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The number of linearly independent vectors in spectral databases

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2009) 5575 LNCS 570-579
DOI: 10.1007/978-3-642-02230-2_58
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Abstract

Linear dependence among spectra in spectral databases affects the eigenvectors obtained from principal component analysis. This affects the values of usual spectral and colorimetric metrics. The effective dependence is proposed as a tool to quantify the maximum number of linearly independent vectors in the database. The results of the proposed algorithm do not depend on the selection of the first seed vector and are consistent with the results based on reduction of the bivariate coefficient of determination. © 2009 Springer Berlin Heidelberg.

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Sáenz, C., Hernández, B., Alberdi, C., Alfonso, S., & Diñeiro, J. M. (2009). The number of linearly independent vectors in spectral databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5575 LNCS, pp. 570–579). https://doi.org/10.1007/978-3-642-02230-2_58

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