Singular value decomposition and its applications
We shall consider a form of matrix factorization known as singular value decomposition (SVD) that is applicable to a general m-by-n matrix. Although still not widely known, the SVD is a powerful method in theoretical and computational analysis of problems involving matrices. It has already found applications in many areas and is of growing importance within and without the circle of numerical mathematics.
SubjectsField of Research::01 - Mathematical Sciences::0103 - Numerical and Computational Mathematics
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