svd_test, a C code which demonstrates the computation of the singular value decomposition and a few of its properties.
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
svd_test m n seedwhere
The computer code and data files described and made available on this web page are 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 a Python version.
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