On the compression of low rank matrices
SIAM Journal on Scientific Computing, 2005•SIAM
A procedure is reported for the compression of rank-deficient matrices. A matrix A of rank k is
represented in the form A=U∘B∘V, where B is ak*k submatrix of A, and U, V are well-
conditioned matrices that each contain ak*k identity submatrix. This property enables such
compression schemes to be used in certain situations where the singular value
decomposition (SVD) cannot be used efficiently. Numerical examples are presented.
represented in the form A=U∘B∘V, where B is ak*k submatrix of A, and U, V are well-
conditioned matrices that each contain ak*k identity submatrix. This property enables such
compression schemes to be used in certain situations where the singular value
decomposition (SVD) cannot be used efficiently. Numerical examples are presented.
A procedure is reported for the compression of rank-deficient matrices. A matrix A of rank k is represented in the form , where B is a submatrix of A, and U, V are well-conditioned matrices that each contain a identity submatrix. This property enables such compression schemes to be used in certain situations where the singular value decomposition (SVD) cannot be used efficiently. Numerical examples are presented.
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