How to test whether a signal is periodic or not?

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    Periodic Signal Test
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Discussion Overview

The discussion revolves around methods to determine whether a given set of discrete data is periodic and how to identify the period if it exists. The focus includes statistical approaches and spectral analysis techniques.

Discussion Character

  • Exploratory, Technical explanation, Debate/contested

Main Points Raised

  • One participant suggests using a statistical regression model with dummy variables to test for periodicity, indicating that significant quarterly dummies would suggest quarterly periodicity.
  • Another participant proposes spectral analysis as a standard method for testing periodic components, recommending the use of tools like FFT and smoothing windows available in statistical software.
  • A third participant provides links to external resources that may contain relevant information about using dummy variables for periodicity testing.

Areas of Agreement / Disagreement

Participants present multiple approaches to testing for periodicity, indicating a lack of consensus on a single method. The discussion remains open with competing views on the best techniques.

Contextual Notes

Some methods mentioned may depend on specific assumptions about the data, such as the choice of regression model or the applicability of spectral analysis techniques. The discussion does not resolve these dependencies.

stevenphy2
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Hi all, let's say I have generated some discrete data as a function of time.
And when I plot it, it looks like that it is periodic.
Is there any scientific way to check whether or not the discrete data is really periodic?
And determine the period, if possible?
Many thanks.
 
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You could define the statistical regression model y = b0 + b1 x + u and then introduce quarterly, monthly, weekly, etc. "dummy variables" into the model. For example, quarterly periodicity will be indicated if the quarterly dummies are significant as a group.
 
The best (and standard) way to test for periodic components is by using spectral analysis. If you are using a statistics/numerics package (like Statistica, Matlab, etc.), then check their tools (FFT, smoothing windows, etc.) for that.
 
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