Professional paper
The singular value decomposition and applications in geodesy
Vida Zadelj Martić
orcid.org/0000-0001-6143-4978
; Faculty of Geodesy, University of Zagreb, Kačićeva 26, 10000 Zagreb
Abstract
The paper considers the singular value decomposition (SVD) of a general matrix. Some immediate applications,
such as determining the spectral and Frobenius norm, rank and pseudoinverse of the matrix are
described. Applications also include approximating the given matrix by a matrix of a lower rank. It is also
shown how to use SVD for solving the homogeneous linear system and the least squares problem. The
paper consists of three parts:
1.) The singular value decomposition,
2.) Some applications of the singular value decomposition,
3.) Applications in geodesy.
Keywords
Singular value decomposition; Unitary matrices; Frobenius norm; Spectral norm; Pseudoinverse; Homogeneous system of linear equations; Least squares problem; Rank
Hrčak ID:
61778
URI
Publication date:
1.12.2010.
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