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Two-Dimensional Singular Value Decomposition: Singular Value Decomposition, Linear Algebra, Matrix Decomposition, Real Number, Complex Number, Matrix, Signal Processing -

English
2026-03-19
€207.26 €259.07

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High Quality Content by WIKIPEDIA articles! Two-dimensional singular value decomposition (2DSVD) computes the low-rank approximation of a set of matrices such as 2D images or weather maps in a manner almost identical to SVD (singular value decomposition) which computes the low-rank approximation of a single matrix (or a set of 1D vectors).In linear algebra, the singular value decomposition (SVD) is an impor ... Full description

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High Quality Content by WIKIPEDIA articles! Two-dimensional singular value decomposition (2DSVD) computes the low-rank approximation of a set of matrices such as 2D images or weather maps in a manner almost identical to SVD (singular value decomposition) which computes the low-rank approximation of a single matrix (or a set of 1D vectors).In linear algebra, the singular value decomposition (SVD) is an important factorization of a rectangular real or complex matrix, with many applications in signal processing and statistics. Applications which employ the SVD include computing the pseudoinverse, least squares fitting of data, matrix approximation, and determining the rank, range and null space of a matrix.

More Information

Publisher OmniScriptum
Release year 2026
Cover type Softcover
EAN 9786131144332
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€207.26 €259.07