NIRS_ICA_V1.0/ica_algorithms/tentative/tdsep/contents.m
% TDSEP ICA tools version 2.01, 2/14/99 by AZ
%
% This is a simple and efficient MATLAB implementation of blind source separation.
% Along the lines of Schuster and Molgedey [1] two (lagged) correlation matrices
% are computed and diagonalized simultaneously using MATLAB's  general eigen-problem solver
% (eig.m). The big problem with this approach is to determine the optimal lag value tau 
% suitable for the given data. Usually tau1=0 and tau2=1 will do, but this is strongly data dependent.
% Therefore, as an extension we developed the TDSEP (Temporal Decorrelation) algorithm, which
% uses _several_ correlation matrices and finds an approximate joint diagonalizer of this 
% matrix set (see Cardosos papers [2] for more details on joint diagonalization)
% See the references below for a description of the TDSEP algorithm [3][4].
% 
% The package includes:
% tdsep2.m      separate instantaneous, linear mixtures of independent
%               sources using an eigen-decomposition of correlation matrices 
% cor2.m        compute time-delayed correlation matrices
% ntu.m         normalize (mixing) matrix to unity (diagonal elements ==1)
% perf.m        evaluate separation performance 
%               by comparing the _estimated_ and the _true_ mixing matrix
% norm_it.m     normalize (mixing) matrix (column vector length =1, e.g. norm(C(:,k),2)==1) 
% sort_norm.m   sort components according to their euclidian norm
% jdiag.m       joint diagonalization of several matrices by J.F. Cardoso
% fischdon.mat  acoustic demo signals (speech and music, 10 sec., sample rate 8kHz)
% sep_demo.m    test routine; run this for a demonstration of blind source separation
%
%
%
%References:
%[1] @Article{Molgedey+Schuster:1994,
%    author      = {L. Molgedy and H.G. Schuster},
%    title       = {Separation of a mixture of independent signals using
%                   time delayed correlations},
%    journal     = {Physical Review Letters},
%    year        = {1994},
%    number      = {72},
%    pages       = {3634-3637} 
%    }
%
%[2] @Article{SC-siam,
%    HTML         = "ftp://sig.enst.fr/pub/jfc/Papers/siam_note.ps.gz",
%    author       = "Jean-Fran\c{c}ois Cardoso and Antoine Souloumiac",
%    journal      = "{SIAM} J. Mat. Anal. Appl.",
%    title        = "Jacobi angles for simultaneous diagonalization",
%    pages        = "161--164",
%    volume       = "17",
%    number       = "1",
%    month        = jan,
%    year         = {1996}
%  }
%
%[3] @TechReport{GMD_REP:Ziehe:1998,
%    type         = {Technical Report},
%    number       = {1998-31},
%    title        = {Artifact Reduction in Magnetoneurography Based on
%                    Time-Delayed Second Order Correlations},
%    author       =  {A. Ziehe and K.-R. M{\"u}ller and G. Nolte 
%                    and B.-M. Mackert and G. Curio}
%    series       =  {GMD Report No. 31},
%    pages        =  {27},
%    year         =  {1998},
%    notes        =  {ISSN 1435-2702}
%  }
%
%[4] @InProceedings{ICANN:Ziehe:1998,
%    title        = {TDSEP - an efficient algorithm 
%                    for blind separation using time structure},
%    author       =  {A. Ziehe and K.-R. M{\"u}ller}
%    booktitle    =  {ICANN'98},
%    address      =  {Skovde},
%    pages        =  {675-680},
%    year         =  {1998}
% } 
%
%
%---------------- (c) 1996-1999 GMD FIRST Berlin, Andreas Ziehe -----------
%                          - All rights reserved -



