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lyngby_svd

(export/lyngby/lyngby_svd.m)


Function Synopsis

[U, S, V] = lyngby_svd(X, arg1, arg2, arg3, arg4, arg5, ...

Help text

 lyngby_svd           - Singular value decomposition

       function [U, S, V] = lyngby_svd(X, ...
          'PropertyName',PropertyValue)

       Input:    X   Matrix. 

       Property: ReduceComponents [ {all} | Integer ] Number of
                                  components to reduce to

       Output:   U   The eigensequence
                 S   Singular values in a vector
                 V   The eigenimages

       Perform singular value decomposition: 

                      X = U * diag(S) * V'

       The returned number of components is the minimum of the rank
       of X and the number specified with the property
       'ReduceComponents'. 

       The singular value decomposition is performed as an eigenvalue
       decomposition on either the inner or the outer product (X*X'
       or X'*X) depending on which one is the computational most
       favorable. 

       See also LYNGBY, LYNGBY_KM_MAIN, LYNGBY_SOP_MAIN,
                LYNGBY_UI_SVD_INIT, LYNGBY_UIS_SVD. 

 $Id: lyngby_svd.m,v 1.11 2002/11/29 18:00:36 fnielsen Exp $

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