- emd: https://www.mathworks.com/help/signal/ref/emd.html
- hht: https://www.mathworks.com/help/signal/ref/hht.html
How to get chaos features from a set of signals to build a ML classifier based on it?
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I have a set of only two categorise time series signals and my supervisor asked me to get the chaos features from it:
he told me first to get the hilbert huang transform, the get the chaos features from its output, but I coulden't fined how to do this
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Answers (1)
Jaynik
on 16 Jul 2024 at 7:14
Hi Mahmoud,
The hht function can be used in MATLAB to obtain the Hilbert-Huang Transform. You will need to give the intrinsic mode function (IMF) as an input. For obtaining IMF, you can perform the Empirical mode decomposition on the time-domain signal using the emd function. Here is a sample code for the same:
% s is time-domain signal
imf = emd(s);
% Compute the Hilbert spectrum of the signal, fs is the sample rate
[hs,f,t] = hht(imf, fs);
You can refer the following documentation to read more about these functions:
Once you obtain the Hilbert spectrum, you can extract the chaos features. You may find the Chaotic Systems Toolbox available on File Exchange to be helpful: https://www.mathworks.com/matlabcentral/fileexchange/1597-chaotic-systems-toolbox
Hope this helps!
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