Code for multivariate denoising in wavelet toolbox

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Ashley Stephenson
Ashley Stephenson el 5 de Jul. de 2016
Hello, I am trying to process EMG signals using the multivariate denoising tool in the wavelet toolbox. I have been unable to export code from the GUI, as this doesn't appear to be an option for this tool, but I would like to duplicate the denoising process in my code in order to process many signals without having to use the GUI for each one. I have provided the relevant section of my code below, as well as a screen shot of the settings I would like to implement as shown in the toolbox.
for channelNum=1:1:8
x = f.emgData(:,channelNum);
% Set the de-noising method parameters.
level = 4;
wname = 'db6';
tptr = 'minimaxi';
sorh = 's';
% Set the PCA parameters
npc_app = 1;
npc_fin = 1;
% Perform multivariate de-noising.
[x_den, npc, nestco] = wmulden(x, level, wname, sym, npc_app, ...
npc_fin, tptr, sorh);
% Add filtered signals to filtered matrix
filtered(:,channelNum) = x_den;
I am essentially trying to apply the settings shown below. When using the parameters above, I do not obtain the same results (filtered signal) as those generated by the GUI, and I'm not sure what I am doing differently. If anyone could help me with this I would appreciate it. Thanks.

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