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Signal gradigram generation

I am trying to create a graph view for my application to find out if there is information that we can extract from the wavelet transform, and not use spectrograms to view what can be obtained using the FFT.

So far, I can take the waveform, and I can perform forward wavelet transform on it. However, I lost the next step. How to include this information in power / energy information? I have a set of waveforms at different frequencies, but I, as I say, have no information about the frequency.

Can someone tell me what is the next step for turning this converted data into a scalogram?

Any help would be greatly appreciated because my google skills do not allow me!

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2 answers

Under reasonable assumptions, the discrete wavelet transform (DWT) decomposes the power / energy / variance of the time series into scales. This energy-saving transformation is that the total dispersion contained in the original time series is contained in quadratic wavelet coefficients (properly normalized), just like DFT! I think that the Wavelet Methods for Time Series Analysis text from Percival and Walden is a great resource for this type of information.

- (CWT) ( DWT) . , , "", (STFT, aka spectrogram).

Torrence Compo - , , . , Matlab CWT .

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http://www.csse.uwa.edu.au/~pk/Research/MatlabFns/FrequencyFilt/scalogram.m

, matlab dsp- , . , dsp , , .

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Source: https://habr.com/ru/post/1742103/

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