compute the singular values/vectors of a numeric matrix
Svd(X, U, V)
n x p matrix
(optional) the left singular vectors are to be returned in U
(optional) the right singular vectors are to be returned in V
Important: The command Svd has been deprecated. Use the superseding command LinearAlgebra[SingularValues] instead.
Svd(X) returns a 1 by min⁡n,p array of the singular values of X.
The entries of X must be all numerical.
Svd(X,U,`left`) returns the singular values and the left singular vectors in U.
Svd(X,V,`right`) returns the singular values and the right singular vectors in V.
Svd(X,U,V) returns the singular values and the left and right singular vectors in U and V respectively. The singular vectors together with the singular values satisfy U'⁢XV=D where U' is the transpose of U and U is n by n, V is p by p, X is n by p, and D is n by p where Di,i is/are the singular value/values of X.
This procedure Svd is compatible with the Fortran library linpack.
Note that nothing happens when the user invokes Svd(X) (same for other calling sequences); the user must use evalf(Svd(X)) to actually compute the singular values and singular vectors.
A ≔ linalg[matrix]⁡2,2,1,2,3,4
A ≔ 1234
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