Signal Analysis: Time Segments & Characteristics

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Discussion Overview

The discussion revolves around analyzing a signal in terms of time segments to understand its characteristics and patterns. Participants explore various methods for frequency and amplitude analysis, including RMS, wavelet transforms, FFT, and spectrograms.

Discussion Character

  • Homework-related
  • Exploratory
  • Technical explanation

Main Points Raised

  • One participant suggests using RMS, wavelet transforms, and FFT for signal analysis but is uncertain which method provides the best understanding.
  • Another participant proposes creating a spectrogram to visualize frequency versus amplitude versus time for frequency analysis.
  • A different participant mentions the Lomb-Scargle Periodogram method as a potential approach to identify underlying frequency components of the signal.
  • A participant shares MATLAB code for FFT analysis, generating power and amplitude spectra, but expresses uncertainty about the correctness of the methods used.
  • One participant provides a link to MATLAB documentation for the spectrogram as a resource for further exploration.

Areas of Agreement / Disagreement

Participants present multiple competing views on the best methods for signal analysis, and the discussion remains unresolved regarding which approach is most effective.

Contextual Notes

The initial problem statement is described as fairly unconstrained, which may limit the applicability of the suggested methods. There is also a lack of clarity regarding the data set being analyzed.

Hzaqa
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Homework Statement


Hi ,
The problem is how to analysis this signal in terms of time segments to understnd the characteristics/pattern of this signal
146493896.png


Homework Equations



There is no relevant equtions

The Attempt at a Solution



I have tried to use :
RMS
Wavlet
FFT
But which one of them can give us a better understing of the system,

Thanks,
 
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Your problem statement is fairly unconstrained so--

For frequency analysis, consider making a spectrogram, a 3 dimensional graph (frequency vs amplitude vs time).

For amplitude analysis, experiment with various moving average (RMS) plots.
 
Presumably you have a data set that corresponds to the graph, and not just the graph alone? You might want to investigate the use of the Lomb-Scargle Periodogram method to tease out the underlying frequency components of the signal.
 
Thanks for the response,


Well, I have applied frequency domain


Matlab code:

m=fft(x)
n=length(x)
power=abs(m(1:floor(n/2))).^2
nyquist=1/2
freq=((1:n/2)/(n/2)*nyquist)*5000
figure
plot(freq,power)
xlabel('Frequency (Hz)')
ylabel('Power')
title('Power Spectrum of Signal')
grid on
977009973.png


amp=abs(m(1:floor(n/2)))
figure
plot(freq,amp)
xlabel('Frequency (Hz)')
ylabel('Amplitude')
title('Amplitude Spectrum of Signal')
grid on
975500764.png





But I am not quite sure which one of them is best/correct,any suggestion,
Thanks
 

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