Matlab Source for PalmPrint Recognition
2016-08-23
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function [U, S, V] = mySVD(X,ReducedDim)
%mySVD Accelerated singular value decomposition.
% [U,S,V] = mySVD(X) produces a diagonal matrix S, of the
% dimension as the rank of X and with nonnegative diagonal elements in
% decreasing order, and unitary matrices U and V so that
% X = U*S*V'.
%
% [U,S,V] = mySVD(X,ReducedDim) produces a diagonal matrix S, of the
% dimension as ReducedDim and with nonnegative diagonal elements in
% decreasing order, and unitary matrices U and V so that
% Xhat = U*S*V' is the best approximation (with respect to F norm) of X
% among all the matrices with rank no larger than ReducedDim.
%
% Based on the size of X, mySVD computes the eigvectors of X*X^T or X^T*X
% first, and then convert them to the eige
%mySVD Accelerated singular value decomposition.
% [U,S,V] = mySVD(X) produces a diagonal matrix S, of the
% dimension as the rank of X and with nonnegative diagonal elements in
% decreasing order, and unitary matrices U and V so that
% X = U*S*V'.
%
% [U,S,V] = mySVD(X,ReducedDim) produces a diagonal matrix S, of the
% dimension as ReducedDim and with nonnegative diagonal elements in
% decreasing order, and unitary matrices U and V so that
% Xhat = U*S*V' is the best approximation (with respect to F norm) of X
% among all the matrices with rank no larger than ReducedDim.
%
% Based on the size of X, mySVD computes the eigvectors of X*X^T or X^T*X
% first, and then convert them to the eige
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