Group: | Linear Algebra |
See also: | eigsm eiggn |
Function: | svd | |
Description: | computes the singular value decomposition of a n x p matrix x (n >= p). The singular value decomposition finds matrices u, l, v such that x = u*l*v' u, v are orthogonal matrices l is a diagonal matrix |
Usage: | y = svd(x) | |
Input: | ||
x | n x p matrix | |
Output: | ||
y.u | n x p matrix, the left matrix u | |
y.l | p vector, elements of the diagonale of matrix l | |
y.v | p x p matrix, the right matrix v |
x = #(1:5)~#(6:10)~#(11:15) y = svd(x) r = x - y.u * (y.l .* y.v') r
Show result in the result matrix
Group: | Linear Algebra |
See also: | eigsm eiggn |