MATLAB Coder problem with discrete wavelet thresholding

2017 6 5
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更新时间：2017 6 14
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Hello everyone. I wanted to generate a C code for my ECG noise removal program with dwt, but I ran into a problem. The Coder doesn't seem to like the wdencmp function. The script is tested, and it is working as intended, I only use the Wavelet toolbox which came with MATLAB, and I checked, all of the functions used are supported for C/C++ generation, and I have enabled the variable-sizing option.
The script is as follows:
function out = denoise(input)
%the thresholding values
thr = [...
0.013347585482866 ; ...
0.015872023591907 ; ...
0.144506458583803 ; ...
0.374411347716711 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ...
];
c = zeros(4170,1);
l = zeros(14,1);
% the deconstruction
[c,l] = wavedec(input,12,'sym4');
% thresholding algorithm
% 1. remove the average value
c(1:l(1)) = zeros(1,l(1));
% apply Heuristic SURE to the detail value
out = wdencmp('lvd',c,l,'sym4',12,thr,'s');
end
What am I overlooking? Any help would be appreciated.
Thanks in advance, Fehér Áron.

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Fehér Áron
Fehér Áron 2017-6-11
Someone? Anything would be helpful for me to somehow break out of this error.

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Fehér Áron
Fehér Áron 2017-6-14

0 个投票

I have finally solved the problem. I've replaced wdencmp with wthcoef and the compiler liked it. Still I have no clue why I got the error, since wdencmp uses wthcoef. Oh well... I am posting the working function if someone needs it.
function out = denoise(input)
%the thresholding values
thr = [...
0.013347585482866 ; ...
0.015872023591907 ; ...
0.144506458583803 ; ...
0.374411347716711 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ; ...
0.000000000000000 ...
];
c = zeros(4170,1);
l = zeros(14,1);
% the deconstruction
[c,l] = wavedec(input,12,'sym4');
% thresholding algorithm
% 1. remove the average value
c(1:l(1)) = zeros(1,l(1));
% apply Heuristic SURE to the detail value
cxc = wthcoef('t',c,l,1:12,thr,'s');
% the reconstruction
lxc = l;
out = waverec(cxc,lxc,'sym4');
end

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