+------------+|    TCA     |+------------+Version 1.0 - September 25th, 2003----------------------------------Description-----------The tca package is a  Matlab program that implements the tree-dependentcomponent analysis (TCA) algorithms that extends the  independent component analysis (ICA), where instead of looking for a linear transformthat makes the data components independent, we are looking for componentsthat can be best fitted in a tree structured graphical model. The TCA modelcan be applied in any situation where the data can be assumed to have beentransformed by an unknown linear transformation.In addition, the TCA algorithm can be specialized to provide a principledway of finding clusters in ICA, where components in the same cluster aredependent, but independent from components in other clusters.The TCA algorithm can be applied to non Gaussian temporally independent sources or Gaussian stationary sources.For more information, please read the following paper:Francis R. Bach, Michael I. Jordan. Beyond independent components: trees and clusters, to appear in Journal of Machine Learning Research, 2003.The tca package is Copyright (c) 2003 by Francis Bach. If youhave any questions or comments regarding this package, or if you want toreport any bugs, please send me an e-mail to fbach@cs.berkeley.edu. Thecurrent version 1.0 has been released on September, 25th 2003. It has beentested on matlab 6.  Check regularly the following fornewer versions: http://www.cs.berkeley.edu/~fbachThe package contains ica code (jader.m) by Jean-Francois Cardoso(cardoso@tsi.enst.fr) and some graphical model utilities from Kevin Murphy (murphyk@ai.mit.edu).Installation------------1. Unzip all the .m files in the same directory2. (Optional) if you want a faster implementation which uses pieces of Ccode: at the matlab prompt, in the directory where the package isinstalled, type: >> mex chol_gauss.cand >> mex chol_hermite.cIt should create compiled files whose extensions depends on the platformyou are using:      Windows: chol_gauss.dll     and  chol_hermite.dll       Solaris: chol_gauss.mexsol  and  chol_hermite.dll      Linux  : chol_gauss.mexglx  and  chol_hermite.dllTo check if the file was correcly compiled, type >> which chol_gauss >> which chol_hermiteand the name of the compiled versions should appear. If you have anyproblems with the C file of if you are using a platform i did notmention, please e-mail me.How to use the tca package---------------------------------The functions that you should use to run the TCA algorithm are'tca', 'cluster_tca', 'tca_statio' and 'cluster_tca_statio' (functions withdefault setting of parameters) and 'tca_options' (where various options can be tried).A detailed description of its options are described insidethe file and can be reached by simply typing 'help tca_options' at thematlab prompt. 3 simple demonstration scripts are provided :'demo_tca1', 'demo_tca2', 'demo_tca3'.NB-1: all the data should be given in columns, that is, if you have mcomponents and N samples, the matrix should be m x N.NB-2: you need to add the three directories 'optimization', 'contrast'and 'utilities' to the MATLAB path, without relative paths(which is done automatically in the demo scripts).