nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

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Bibliographic Details

Title: Two-Dimensional Singular Value Decomposition : Singular Value Decomposition, Linear Algebra, Matrix Decomposition, Real Number, Complex Number, Matrix, Signal Processing
Publisher: Omniscriptum
Publication Date: 2026
Language: English
ISBN 10: 6131144338
ISBN 13: 9786131144332
Binding: Taschenbuch
Condition: Neu
Dimensions: 220 millimeters width by 150 millimeters height by 9 millimeters depth
Weight: 233 grams

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