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ExperimentA1.m
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ExperimentA1.m
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load('BaseParams.mat')
time = 0:1:128;
dictfn = @(numModes) SinCosWindowedDictEven(numModes, time);
dataname = 'Figure5Data';
% note: no noisefn because already added noise (so that exactly same across
% methods)
max_iter = 12; % for the sake of Figure6
numTrials = 1;
errors = zeros(numTrials, 1);
corrs = zeros(numTrials, 1);
sparsities = zeros(numTrials, 1);
numModes = 40000;
expnum = 'A1';
for t = 1:numTrials
[errors(t), corrs(t), sparsities(t)] = BaseExperiment(decompfn, dictfn, dataname, initfnA, ...
initfnB, initfnZ, noisefn, numModes, Zthresholdfn, max_iter, lowtau, ...
hightau, perturbAfn, perturbBfn, perturbZfn, expnum, t, ...
lenSqn, slopeThreshold, diffThreshold);
end
csvwrite(sprintf('./exp%s/summary.csv',expnum),[errors, corrs, sparsities])