68 lines
2.1 KiB
Matlab
68 lines
2.1 KiB
Matlab
function [newVectors, whiteningMatrix, dewhiteningMatrix] = whitenv ...
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(vectors, E, D, s_verbose);
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%WHITENV - Whitenv vectors.
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%
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% [newVectors, whiteningMatrix, dewhiteningMatrix] = ...
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% whitenv(vectors, E, D, verbose);
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%
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% Whitens the data (row vectors) and reduces dimension. Returns
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% the whitened vectors (row vectors), whitening and dewhitening matrices.
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%
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% ARGUMENTS
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%
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% vectors Data in row vectors.
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% E Eigenvector matrix from function 'pcamat'
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% D Diagonal eigenvalue matrix from function 'pcamat'
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% verbose Optional. Default is 'on'
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%
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% EXAMPLE
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% [E, D] = pcamat(vectors);
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% [nv, wm, dwm] = whitenv(vectors, E, D);
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%
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%
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% This function is needed by FASTICA and FASTICAG
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%
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% See also PCAMAT
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% 24.8.1998
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% Hugo Gävert
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% ========================================================
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% Default value for 'verbose'
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if nargin < 4, s_verbose = 'on'; end
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% Check the optional parameter verbose;
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switch lower(s_verbose)
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case 'on'
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b_verbose = 1;
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case 'off'
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b_verbose = 0;
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otherwise
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error(sprintf('Illegal value [ %s ] for parameter: ''verbose''\n', s_verbose));
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end
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% ========================================================
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% Calculate the whitening and dewhitening matrices (these handle
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% dimensionality simultaneously).
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whiteningMatrix = inv (sqrt (D)) * E';
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dewhiteningMatrix = E * sqrt (D);
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% Project to the eigenvectors of the covariance matrix.
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% Whiten the samples and reduce dimension simultaneously.
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if b_verbose, fprintf ('Whitening...\n'); end
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newVectors = whiteningMatrix * vectors;
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% ========================================================
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% Just some security...
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if max (max (imag (newVectors))) ~= 0,
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error ('Whitened vectors have imaginary values.');
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end
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% Print some information to user
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if b_verbose
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fprintf ('Check: covariance differs from identity by [ %g ].\n', ...
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% Added by DR for "Octave" compatibility:
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% Normalize the covariance matrix by N, not by N-1:
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max (max (abs (cov(newVectors')*((size(newVectors',1)-1)/size(newVectors',1)) - eye (size (newVectors, 1))))));
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end
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