Signal Detection in Singular Value Decomposition
Abstract
We develop an Iterative version of the Singular Value Decomposition (ISVD) that jointly analyzes a finite number of data matrices to identify signals that correlate among the rows of matrices. It will be illustrated how the supervised analysis of a big data set by another complex, multi-dimensional phenotype using the ISVD algorithm could lead to signal detection.
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