Feature extraction using DWT and WPT

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?

[Tubi]

Any comment, please. I will be very happy with any comments or correction.

[Bernhard Suhm]

There is nothing obviously wrong with what you do or your result. If you provided your data, maybe we could tell more.

[shivu shetty]

can i get that feature extraction using wavelet code

[Rasheed Majeed]

Dear Tubi

I think you have some error in subplot , Index must be a 3 -digit number of the format mnp

[Rasheed Majeed]

Sorry dear Tubi

Your expression for subplot is Correct .

Answer 1

[Bernhard Suhm]

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.