runSvdLda

%% Making data as
%%   trials{task,trial}  each is nchannels x nsamples matrix
%%   classes

0001 %%% Making data as
0002 %%%   trials{task,trial}  each is nchannels x nsamples matrix
0003 %%%   classes
0004 clear trials classes parameterSets;
0005 load_eegdata;
0006 
0007 subject = 1
0008 tasks = [1 2 3 4 5]
0009 trials = 1:5
0010 trials = squeeze(eegdata(subject,tasks,trials));
0011 % Remove EOG channel
0012 [nr,nc] = size(trials);
0013 for r = 1:nr
0014   for c = 1:nc
0015     trials{r,c} = trials{r,c}(1:6,:);
0016   end
0017 end
0018 
0019 classes = repmat((1:length(tasks))',1,length(trials));
0020 
0021 %%% Setting up matrix of parameter values
0022 lags = 0:4;
0023 nchannels = 6;
0024 winShift = 32;
0025 k = 0;
0026 for winSize = [62 125]
0027   for nl = 0:lags
0028     for nModes = 1:nchannels*(nl+1)
0029       for firstMode = 1:(nchannels*(nl+1))-nModes+1
0030     k = k + 1;
0031     parameterSets(k).nlags = nl;
0032     parameterSets(k).winSize = winSize;
0033     parameterSets(k).winShift = winShift;
0034     parameterSets(k).firstMode = firstMode;
0035     parameterSets(k).nModes = nModes;
0036       end
0037     end
0038   end
0039 end
0040 
0041 %%% Run all experiments
0042 valreps = 5;
0043 CV = general(trials,classes,parameterSets,0.2,valreps,...
0044     @makeSVDModes,@LDA,@selectModes);
0045   
0046 %%% Display results
0047 
0048 summarizeTestResults(CV);