www.pudn.com > FastICA_2.1.zip > gui_help.m
function gui_help(which_help)
%
% Used by FASTICAG
% All the help texts and title used by GUI are stored here.
% Make changes here.
% Also displays the helpwindow with the selected text
% Hugo Gävert
% 15.1.2001
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switch which_help
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case 'pcamat'
helptitle = 'FastICA: Reduce dimension';
helptext=[ ...
'You may reduce the dimension of the data by selecting only the '
'subspace corresponding to certain eigenvalues of the covariance '
'matrix of the data. Give the indices of the first and last '
'eigenvalues (sorted in descending order) to be included (all '
'eigenvalues in between will be included as well). The eigenvalues '
'and their indices can be seen in the graphical plot now on the '
'screen. The heights of the bars give the eigenvalues, with indices '
'below. '
' '
'For example, give ''1'' and ''n'' if you want to reduce the dimension '
'to n by principal component analysis, which means discarding the '
'subspaces corresponding to the smallest eigenvalues. Such a '
'dimension reduction may reduce noise and improve the performance of'
'ICA. '];
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case 'gui_cb_about'
helptitle='About FastICA';
helptext =[ ...
'FastICA for Matlab 5.x '
'Version 2.1, January 15 2001 '
'Copyright (c) Hugo Gävert, Jarmo Hurri, Jaakko Särelä, and Aapo Hyvärinen.'
' '
'For more information please see: '
'http://www.cis.hut.fi/projects/ica/fastica/ '];
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case 'gui_cb_help'
helptitle='FastICA GUI';
helptext = [...
'Basic function: '
' '
'- Click LOAD DATA and give the name of the variable that contains '
' the data. '
' '
'- Click DO ICA to perform the analysis. '
' '
'- Click SAVE RESULTS to store the results for future use. '
' '
'Options: '
' '
'If the input matrix contains the signals as column vectors instead of '
'row vectors, click on TRANSPOSE to transpose the data matrix. '
' '
'Click on PLOT DATA to see the data as 1-D time signals. '
' '
'Clicking REDUCE DIM gives you a graphical plot of the eigenvalue '
'structure of the covariance matrix of the data. You can then reduce '
'the dimension of the data by retaining only the subspaces corresponding to '
'the largest (or smallest) eigenvalues (i.e. variances). To undo this '
'operation click ORIGINAL DIM. You can plot the whitened (preprocessed '
'data) by PLOT WHITENED. '
' '
'Click on DO ICA to perform independent component analysis. '
'Clicking on PLOT ICS has the same effect, except that DO ICA forces '
'recomputation of ICA. '
' '
'You can choose the decorrelation approach by the ''Approach'' drop-down menu:'
'deflation means that the independent components are estimated '
'one-by-one, whereas in the symmetric approach they are estimated in '
'parallel. You can now choose the number of independent components to be '
'estimated in both deflation and symmetric approaches. '
' '
'You have a choice of three nonlinearities: '
' '
'''pow3'' (default) : g(u)=u^3 '
'''tanh'' : g(u)=tanh(u) '
'''gauss'' : g(u)=u*exp(-u^2/2) '
'''skew'' : g(u)=u^2 '
' '
'For example, you could choose approach=''symmetric'' and nonlinearity=''tanh'' '
'to perform maximum likelihood ICA estimation for supergaussian data. '
' '
'If the algorithm does not seem to converge, you can use the stabilized '
'version of the fixed-point algorithm. To use the stabilized version, '
'choose ''on'' from the drop-down menu ''Stabilization''. '
'If you have specified a value less than 1 for the parameter ''mu'' from '
'the ''Advanced Options'' menu then the ''Stabilization'' drop-down menu is '
'not active. This is because if the parameter ''mu'' is less than 1 then the '
'program will use the stabilized code. Please see the help for '
'Advanced Options for more information about stabilization. '
' '
'The ADVANCED OPTIONS menu has its own HELP button. '
' '
'During computations, an INTERRUPT button appears. Clicking the button '
'interrupts the computations. '];
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case 'gui_advc'
helptitle='FastICA GUI: Advanced options';
helptext = [...
'Advanced options: '
' '
'In some cases, it may be desired to improve the statistical '
'performance of the algorithm by using a fine-tuning procedure. This '
'means that after (initial) convergence, the algorithm is run '
'(possibly) with a different nonlinearity, and using a smaller step '
'size and the stabilized version of the fixed-point algorithm. '
'You can specify the nonlinearity that will then be used with the '
'parameter ''Finetune''. If you set the the finetuning to ''off'', then the'
'fine-tuning won''t be done. '
' '
'You can also fine-tune the nonlinearities used in the fixed-point '
'algorithm. '
'The nonlinearities tanh and gauss contain parameters a1 and a2, so '
'that the nonlinearities are in fact defined as: '
'''tanh'' : g(u)=tanh(a1*u) '
'''gauss'' : g(u)=u*exp(-a2*u^2/2) '
'The default values of a1 and a2 are 1, in which case they effectively '
'disappear from the definitions. '
' '
'If the algorithm does not seem to converge, you can use the stabilized'
'version of the fixed-point algorithm. There are two ways of doing '
'this. The first one is to explicitly specify the value of the step '
'size parameter ''mu''. The default value is 1. Choosing a value that '
'is smaller than 1 implies that the computations are made using the '
'stabilized fixed-point algorithm. The second way to use the stabilized'
'version is simpler: choose ''on'' in the drop-down menu ''stabilization'' '
'(on the main menu page). Then the value of mu will be changed '
'automatically during the ICA calculations. If the program senses that '
'the algorithm is stuck between two points, it will halve the value of '
'mu (.5 * mu) for duration of one round. (This is called a ''stroke.''). '
'Also if there is no convergence before half of the maximum number of '
'iterations has been reached then the mu will be halved for the rest '
'of the rounds. '
' '
'The parameter ''epsilon'' is used to decide if the algorithm has '
'converged. A larger epsilon makes the convergence test less strict. '
'Note that if you use finetuning or stabilization, epsilon may need to '
'be reduced accordingly. '
' '
'''Maximum number of iterations'' gives the absolute maximum of '
'iterations used in the estimation procedure. In the deflation '
'approach, this is iterations per component. '
' '
'You can input the ''Initial state'' of the algorithm, i.e. the initial '
'value for A. Choose ''guess'' in the drop-down menu ''Initial state'', '
'click on ''Load Initial guess'', and give the name of the variable in '
'Matlab workspace that contains the initial value. '
' '
'In the drop-down menu ''Display mode'' you can choose if the results are'
'plotted during computations. You may wish to switch this off '
'especially if you have lots of data which takes a long time to plot. '
'''Iteration between displays'' tells how often the running estimates of '
'the independent components are plotted: A value of 1 means after every'
'iteration. '
' '
'If the data vector is very long (more than 10 000 points), it may be '
'advisable to use only a part of the data at every iteration. The '
'option ''Sample size'' allows you to give the proportion (0-1) of the '
'data that is used at every step. The sample is chosen randomly at '
'every step. '
' '
'Click on DEFAULT to return to default values for all advanced options.'
'You can make the new values take effect without closing the window by '
'clicking APPLY. '];
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case 'gui_lc_data'
helptitle='FastICA GUI: Load data';
helptext = [...
'Input the name of the variable in Matlab workspace that contains the '
'data. The data must be in a single matrix, each row (or column) giving'
'the values of one signal. If the signals are in column vectors, click '
'TRANSPOSE after loading the data to transpose the data matrix. '
' '
'If the data is in a file, load it to Matlab workspace first. '];
case 'gui_lc_guess'
helptitle='FastICA GUI: Load guess';
helptext = [...
'Input the name of the variable in Matlab workspace that contains the'
'initial value for the mixing matrix A, and click OK. If the initial '
'value is in a file, load it to Matlab workspace first. '];
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case 'gui_sc'
helptitle='FastICA GUI: Save results';
helptext = [...
'The results will be saved as variables in Matlab workspace. '
'You give a suffix that identifies the variables. For example, if you '
'give ''_FASTICA'', the results will be stored in the following variables:'
' '
'W_FASTICA : estimate of the separating matrix '
'A_FASTICA : estimate of the mixing matrix '
'IC_FASTICA : estimated independent components (row vectors) '
' '
'Additional results related to preprocessing: '
'D_FASTICA and E_FASTICA : give the eigenvalue decomposition of the '
' covariance matrix '
'whiteningMatrix_FASTICA : matrix performing whitening and dimension '
' reduction '
'dewhiteningMatrix_FASTICA : the pseudoinverse of the whitening matrix '
'whitesig_FASTICA : whitened (i.e. preprocessed) signals. '];
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end
helpwin(helptext, helptitle);