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I am looking into exponentially damped signals where it is a stationary signal (after implementing the Adfuller statistical test) and I would like to look into how can I extract meaningful features out of the signal in order to do pattern recognition with machine learning. Can anyone guide me on where I can find articles/blogs of signal processing techniques and feature extraction of exponentially damped signal?

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  • $\begingroup$ Can you share a bit more information about the problem? Specifically, what sort of "features" of the exponential signal are you after? E.g. amplitude, rate of decay of each sinusoid? Something else?) $\endgroup$ – A_A Apr 1 at 9:11
  • $\begingroup$ @A_A relating to damping of the signal, what kind of feautres can I extract from it $\endgroup$ – Lenman147 Apr 1 at 10:09
  • $\begingroup$ If its a sinusoid damped by an exponential, you can extract the frequency of the sinusoid by taking the peak of the fft and then use it to calculate the damping factor. $\endgroup$ – DSP Novice Apr 1 at 12:06
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    $\begingroup$ Does this answer your question? How to recover frequency and damping coefficient from superposition of damped oscillators? $\endgroup$ – A_A Apr 2 at 9:13
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    $\begingroup$ @DSPNovice Well, how can I extract features from STFT? And I also know about wavelet and HHT, what are the uses of both algorithms and how to also extract features from it? $\endgroup$ – Lenman147 Apr 3 at 11:35

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