The singular value decomposition and applications in Geodesy (CROSBI ID 173363)
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Zadelj-Martić, Vida
engleski
The singular value decomposition and applications in Geodesy
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 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
Singular value decoposition; Unitary matrices; Frobenius norm; Spectral norm; Pseudoinverse; Homogeneous system of linear equations; Least squares problem; Rank
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