www.gusucode.com > matlab编程盲源分离程序 实现了EFICA、WASOBI、COMBI等算法源码程序 > matlab编程盲源分离程序 实现了EFICA、WASOBI、COMBI等算法源码程序/BSSGUIlunwen/bssg/bssgui_help.m
function bssgui_help(keyword)
switch keyword
case 'about'
helptitle = 'About BSSGUI';
helptext = [...
'X=======================================================================X'
'| BSSGUI: Interactive GUI for BSS algorithms control |'
'X-----------------------------------------------------------------------X'
' '
' GUI by: Jakub Petkov '
' e-mail: bssgui@centrum.cz '
' homepage: http://bssgui.wz.cz/ '
' last modified: 2008-10-07 '
' version: 2.0 '
' '
'-------------------------------------------------------------------------'
' by J. Petkov (c) 2008 '
'-------------------------------------------------------------------------'];
case 'description'
helptitle = 'Description of BSSGUI';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Description of BSSGUI '
' --------------------- '
' '
' BSSGUI is a Graphical User Interface (GUI) for control of BSS algorithms'
' EFICA, WASOBI, COMBI, MULTI-COMBI, FCOMBI, BGL and Extended EFICA. '
' It was designed in/for MATLAB 7.1 Release R14SP3. Most of all important '
' functions are controlled in a main window. The window is divided into 3 '
' main parts. The first one enables to work with input (source) data, '
' the second one enables algorithms selection and setting their parameters'
' and the last one enables other function, as for saving and working with '
' output data and containing important Test data function. '
' '
' The BSSGUI is provided in a package containing lightly adjusted M-files '
' of used algorithms. The application uses msplot(x), showmatrixISR(x) '
' and gengau(x) functions as well. '
' '
' The package contains large detailed HELP support area that makes using '
' the GUI more comfortable. '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'guide'
helptitle = 'Quick-start guide';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Quick-start guide '
' ----------------- '
' '
' If you want to use the BSSGUI and try to practice blind source separation '
' without any knowledge about this problem, you can just follow these steps:'
' '
' 1) Loading data '
' - Press the LOAD DATA button in the main window of the application. '
' - Choose a variable containing source data. (loaded from base '
' workspace of Matlab) '
' - Confirm loading by pressing the button LOAD. '
' - Check if a number of signals and a number of samples comes true. '
' If not, press the TRANSPOSE button to do the transposition. '
' - Input data can be visualy checked by pressing the PLOT DATA button.'
' '
' 2) Running the separation '
' - Select the desired algorithm. (EFICA is default) '
' - You do not have to set any of its parameters. There are defined '
' default values, that are optimal for the common separation. '
' - Press the RUN BUTTON to run the separation. '
' '
' 3) Working with outputs '
' - Press the VIEW ISR button to see the correctness of separation. '
' (dark fields represent worse separation; black fields mean '
' nonseparability of concrete components) '
' - Press the PLOT RESULTS button to see graphical results of '
' separation. (to check results of separation visualy) '
' - Presssing the SAVE RESULTS button enables you to save all results '
' in the base workspace of Matlab or to a user-named file. Just '
' choose desired destination and type name of variable or file or use'
' clicking the Default button to load pre-defined values of names. '
' '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'input'
helptitle = 'Input (source) data';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Input (source) data '
' ------------------- '
' '
' The BSSGUI package works with arbitrary data organized into row vectors '
' saved in variables in the base workspace of Matlab. It can be loaded by '
' pressing the LOAD DATA button. '
' '
' If the matrix of imported source data is organized into a set of column '
' vectors (check indication in the main window of the application), it can'
' be transposed by pressing the TRANSPOSE button. '
' '
' '
' Examples '
' -------- '
' '
' 1) The easiest way how to create data convenient for practicing the '
' separation is to use this command: '
' '
' x=rand(5,1000); '
' '
' It generates a matrix of source data which contains 5 source signals '
' with 1000 samples. This variable can be used for practicing the '
' separation. But of course, separation using this generated data is '
' not illustrative. '
' '
' 2) Advanced users can try to generate data prepared specially for each '
' algorithm they are going to use. That means: '
' '
' Lets generate source signals first. '
' '
' s(1,:)=rand(1,1000); % uniform distribution '
' s(2,:)=sign(randn(1,1000)); % binary distribution '
' s(3,:)=randn(1,1000); % gaussian distribution '
' s(4,:)=randn(1,1000); % gaussian distribution '
' '
' Now generate random matrix A which represents system, where the '
' source signals s (defined above) are mixed. Dimension of matrix must '
' be equal to the number of source singals. '
' '
' A=rand(4); '
' '
' Using following multiplication creates matrix of unknown mixed '
' signals x. '
' '
' x=A*s; '
' '
' Load variable x in the GUI by pressing the LOAD DATA button. Now you '
' can consider which algorithm to use. Our aim is to get back the '
' source signals without knowledge of system A, just only by running '
' one of algorithms so we can delete the matrix A from workspace (to '
' trust that it really works). '
' '
' clear A; '
' '
' Using one of algorithms on data x gets back a demixing matrix W which'
' multiplicated by mixed signals gets back estimated appearance sw of '
' source signals s. '
' '
' sw=W*x; '
' '
' If the separation was 100% succesful data s is equal to sw. Of course'
' that is an impossible situation in real separation because the '
' demixing matrix cannot be calculated but only estimated by used '
' algorithm. '
' '
' '
' See also: '
' '
' Help -> Data -> Load data '
' (to see how to load data and how to work with built in demo '
' signals generator) '
' '
' Help -> Algorithms -> Run algorithm '
' (to get more information about how to run the separation) '
' '
' Help -> Plot and view -> Plot source data '
' (to check visualy appearance of source data) '
' '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'load'
helptitle = 'Load data procedure';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Data loading '
' ------------ '
' '
' To load input (source) data you want to separate click the button marked'
' as LOAD DATA. There will appear new window where you can select your '
' variable previously saved in the base workspace. '
' '
' Confirm data loading by pressing the LOAD button. '
' '
' If your variable does not appear in the window, its name may be '
' identical to some of the system variables of BSSGUI. Try to change the '
' name of your variable. '
' '
' Forbidden names of variables: '
' X, dim, N, nastaveni, was_temp, AR_order '
' '
' '
' Example signals (USE DEMO button) '
' --------------------------------- '
' '
' If you are not sure what kind of data you should use to try the BSSGUI '
' for the first time, you can use example signals generator. '
' '
' Pressing the USE DEMO button starts the example signals generator which '
' creates 3 independent signals with length of 1000 samples mixed by '
' randomly generated mixing matrix A. The source signals are '
' '
' s(1,:)=sinusoid; '
' s(2,:)=rectangle; '
' s(3,:)=saw; '
' '
' After running the separation you should be able to observe these three '
' components of signals by pressing the PLOT RESULTS button. '
' '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'transpose'
helptitle = 'Transpose data';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Transpose data '
' -------------- '
' '
' BSSGUI works with input matrix of source data organized into a set of '
' row vectors. If your variable consists of a set of column vectors, it '
' can be transposed by pressing the TRANSPOSE data button. '
' '
' After loading the data you may check organization of you loaded variable'
' in the main window of BSSGUI in a panel marked as Mixed signals. Please '
' check if the number of signals and number of samples are equal to the '
' reality. If the values dismatch use the TRANSPOSE button to make the '
' correction. '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'output'
helptitle = 'Output data (results)';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Output data '
' ----------- '
' '
' The output of the separation is expressed in two ways: '
' '
' 1) ISR matrix '
' - ISR = Interference-to-Signal Ratio '
' - represents a criterion of correctness of the separation '
' - obtained as a square matrix consisting of zeros in the diagonal '
' (expressed by white fields) '
' - after running the separation, press button VIEW ISR to obtain '
' the ISR matrix plot in grey spectrum, which tells us, how '
' successful was the separation -> the darker fields the worse '
' correctness of separation (black fields say that the components '
' were not separated) '
' '
' 2) Estimation of demixing matrix '
' - marked as W '
' - if multiplied by mixed source data gives us matrix of separated '
' signals (estimation of original source data) '
' '
' Both of these output matrices can be saved in the base workspace or '
' in user-defined file. '
' '
' '
' See also: '
' '
' Help -> Data -> Save data '
' (to see how to work with save data functions) '
' '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'save'
helptitle = 'Saving data';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Save data '
' --------- '
' '
' Results of the separation (ISR matrix and estimation of demixing matrix '
' W) can be optionally saved into variables in the base workspace or to '
' user-selected file. '
' '
' Follow these steps: '
' '
' 1) Choose one of the possibilities ''To workspace'' or ''To file'' '
' 2) Type name of your variable or file. The fields can be filled '
' automaticaly by predefined vaues after pressing the DEFAULT button.'
' 3) Press the SAVE data button. '
' '
' '
' See also: '
' '
' Help -> Data -> Output data (results) '
' (to get more information about the data to save) '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'EFICA'
helptitle = 'EFICA algorithm';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' EFICA '
' ----- '
' '
' Algorithm based on the Independent Component Analysis (ICA) therefore '
' it is convenient to use it for separating the non-Gaussian i. i. d. '
' signals. Other important condition is independence of signal components.'
' Main principle of separation is minimalization of mutual information. '
' '
' '
' Settings (parameters) '
' --------------------- '
' '
' SaddleTest: test of saddle points '
' (true/false) '
' '
' Nonlinearity: type of nonlinearity '
' (rat1, rat2 - polynomial '
' tanh - hyperbolic tangential '
' gaus - gaussian) '
' '
' Starting point: starting point of iteration '
' (randn(dim) - randomly generated matrix '
' eye(dim) - eye matrix) '
' '
' Epsilon: very low value which doesn''t allow to stop '
' iteration until changes in estimated demixing '
' matrix are above this value (stop criterion) '
' '
' FineEpsilon: value used by finetuning to refine on '
' a calculation (stop criterion for post '
' estimation) '
' '
' MaxIt: maximum number of FastICA iterations '
' '
' MaxItAfterSaddleTest: maximum number of iterations after a saddle '
' point was indicated '
' '
' FinetuneMaxIt: maximum number of improving iterations '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'WASOBI'
helptitle = 'WASOBI algorithm';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' WASOBI '
' ------ '
' '
' This algorithm works with stationary stochastic Gaussian processes. '
' Very important condition for using algorithm WASOBI is the spectral '
' difference of input signals. The algorithm exploits the time structure '
' of the signal sources and ignores the sources'' statistical '
' distributions. '
' '
' '
' Settings (parameters) '
' --------------------- '
' '
' AR order: maximum AR order of the separated sources '
' '
' Stabilization: constant that may help to stabilize the '
' algorithm. It has the meaning of maximum '
' magnitude of poles of the AR sources. '
' (rmax=1 - no stabilization is applied '
' rmax=0.99 - most stable results) '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'COMBI'
helptitle = 'COMBI algorithm';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' COMBI '
' ----- '
' '
' This algorithm is used for separating more complicated source signals. '
' It means that the input signals consist of data with both dimensional '
' and time structure. It is unable to separate such signals by applicating'
' only one of the algorithms EFICA or WASOBI. '
' '
' The COMBI algorithm was developed as an efficient combination of '
' algorithms EFICA and WASOBI. In principle, COMBI reads the source '
' signals and analyses which part of the input data is convenient to '
' separate with each of the two methods. '
' '
' '
' Settings (parameters) '
' --------------------- '
' '
' COMBI uses elementary predefined settings of algorithms EFICA and '
' WASOBI. '
' '
' '
' See also: '
' '
' Help -> Algorithms -> EFICA '
' (to get more information about used parameters) '
' '
' Help -> Algorithms -> WASOBI '
' (to get more information about used parameters) '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
case 'gendata'
helptitle = 'Data generator';
helptext = [...
'X=======================================================================X '
'| BSSGUI: Interactive GUI for BSS algorithms control | '
'X-----------------------------------------------------------------------X '
' '
' Data generator '
' -------------- '
' '
' for i=1:number_of_trials '
' for j=1:number_of_signals '
' '
' s(:,i)=filter([1 1],[1],gengau2(1,1,1000)); '
' '
'------------------------------------------------------------------------- '
' by J. Petkov (c) 2008 '
'------------------------------------------------------------------------- '];
% dal氻 zaj韒av mo瀗osti helpu
% case 'A'
% helptitle = 'Matrix A';
% A = evalin('base', 'A');
% helptext = [num2str(A)];
% case 'B'
% web \index.html
end
helpwin(helptext, helptitle);