| MATLAB Functions | Help Desk |
svds
A few singular values
[U,S,V] = svds(A,k)
[U,S,V] = svds(A,k)
computes the k largest singular values and singular vectors of the matrix A. k = 5 is the default. If A is m-by-n, then U is m-by-k with orthonormal columns, S is k-by-k diagonal, V is n-by-k with orthonromal columns, and U*S*V' is the closest rank k approximation to A.
[U,S,V] = svds(A,k,0)
computes the k smallest singular values and singular vectors.
s = svds(A,k,...)
returns just a vector of singular values.
svd Singular value decomposition
eigs Find a few eigenvalues and eigenvectors