svd_test a MATLAB code which calls svd(), which computes the singular value decomposition (SVD) of a matrix.
The singular value decomposition has uses in solving overdetermined or underdetermined linear systems, linear least squares problems, data compression, the pseudoinverse matrix, reduced order modeling, and the accurate computation of matrix rank and null space.
The singular value decomposition of an M by N rectangular matrix A has the form
A(mxn) = U(mxm) * S(mxn) * V'(nxn)
where
The information on this web page is distributed under the MIT license.
svd_test is available in a C version and a C++ version and a Fortran90 version and a MATLAB version and an Octave version and a Python version.
fingerprints, a dataset directory which contains a few images of fingerprints.
svd_basis, a MATLAB code which computes a reduced basis for a collection of data vectors using the singular value decomposition (SVD).
svd_faces, a MATLAB code which applies singular value decomposition (SVD) analysis to a set of images.
svd_fingerprint, a MATLAB code which reads a file containing a fingerprint image and uses the singular value decomposition (SVD) to compute and display a series of low rank approximations to the image.
svd_gray, a MATLAB code which reads a gray scale image, computes the singular value decomposition (SVD), and constructs a series of low rank approximations to the image.
svd_lls, a MATLAB code which uses the singular value decomposition (SVD) to construct and plot the best affine and linear relationships in the sense of least square, between two vectors of data.
svd_powers, a MATLAB code which applies singular value decomposition (SVD) analysis to powers x(i)^(j-1).
svd_snowfall, a MATLAB code which reads a file containing historical snowfall data and analyzes the data with the singular value decomposition (SVD).
svd_sphere, a MATLAB code which analyzes a linear map of the unit sphere caused by an arbitrary 3x3 matrix A, using the singular value decomposition (SVD).
svd_truncated_test, a MATLAB code which demonstrates the computation of the reduced or truncated singular value decomposition (SVD) that is useful for cases when one dimension of the matrix is much smaller than the other.