Feature extraction using DWT and WPT

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Tubi
Tubi on 17 Feb 2018
Commented: Rasheed Majeed on 16 Sep 2021
Hi,
Can anyone confirm if my method of feature extraction is correct or not? I have used DWT and later WPT to decompose and extract features from vibration signals.
For DWT, I used the following MATLAB functions:
Example:
x1= signal;
[cA1,cD1]= wavedec(x1,1,'db4');
...
plot(cA1); title('Level-1 Approximation Coefficients')
figure(1); subplot(313);
plot(cD1); title('Level-1 Detail Coefficients')
k1=kurtosis(cA1) %E.g of one parameter used to extract some features%Approximation%
k2=kurtosis(cD1) %details%
...
And other statistical parameters.
My extracted features, after being used as inputs for the ANN classifier, showed that approximations are better than details, and performed with a very high classification rate.
I haven't found a reason to reconstruct the signal or using any filters (i.e. Low and high filters)?!
MATLAB staff and experts, can you confirm my method or correct me please?
  5 Comments
Rasheed Majeed
Rasheed Majeed on 16 Sep 2021
Sorry dear Tubi
Your expression for subplot is Correct .

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Answers (1)

Bernhard Suhm
Bernhard Suhm on 25 Mar 2018
You could try using wavelets, the basic documentation is here: https://www.mathworks.com/help/wavelet/ref/dwtfilterbank.wavelets.html. That requires the Wavelet toolbox though, which you could get via a trial.

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