# Problems with signal processing

4 views (last 30 days)
Dan Lecoutre on 24 Mar 2023
Commented: Star Strider on 28 Mar 2023
I have a signal as shown here:
The x axis is just the sample number and the y is the ampltiude of the signal in volts.
There are ten 'bursts' where the amplitude of the signal spikes and dies out before rising again. I would like to obtain the fast fourier transform of each of these 10 bursts individually and plot them on the same figure. I'm not entirely sure where to start and any help would be greatly appreciated. Star Strider on 24 Mar 2023
For a time-frequency plot, I would use the pspectrum function with the 'spectrogram' option, at least for an initial approach, although that might be all you need. (The pspectrum results are a bit easier to interpret than the spectrogram results.)
Star Strider on 28 Mar 2023
Here are three ways of depicting it, demonstrating the time-frequency characteristics of the spike —
burst1 = LD.burst1;
Fs = 1; % Assume Default Sampling Frequency (Value NMot Provided)
[p,f,t] = pspectrum(burst1, Fs, 'spectrogram');
figure
waterfall(f,t,p.')
set(gca,XDir="reverse",View=[60 60])
ylabel("Time (s)")
xlabel("Frequency (Hz)")
xlim([0 Fs*0.01])
ylim([0 max(ylim)/3])
colormap(turbo) figure
surfc(f,t,p.', 'EdgeColor',[1 1 1]*0.5)
set(gca,XDir="reverse",View=[60 30])
ylabel("Time (s)")
xlabel("Frequency (Hz)")
xlim([0 Fs*0.01])
ylim([0 max(ylim)/3])
colormap(turbo) figure
contourf(f,t,p.')
set(gca,XDir="reverse")
ylabel("Time (s)")
xlabel("Frequency (Hz)")
xlim([0 Fs*0.005])
ylim([max(ylim)/10 max(ylim)/4])
colormap(turbo) It would help to have the sampling frequency (I did not find it anywhere) however the plots should scale with it.
Ths Z-axis units are in terms of power, not decibels. Use the pow2db function to convert them, if desired.
.

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