Power analysis of low frequency component

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SUMMARY

The discussion centers on measuring the power of low-frequency periodic events (~0.2Hz) in voltage-time signals, specifically addressing the ideal window size for power spectral density (PSD) analysis. The user inquires whether the window size should be based on the frequency (1/0.2Hz) or the duration of the event (30ms). Dan suggests two approaches: averaging the events and calculating the PSD of the average or calculating the PSD for each event and then averaging the results. This indicates that both methods can be valid depending on the analysis goals.

PREREQUISITES
  • Understanding of power spectral density (PSD) analysis
  • Familiarity with low-frequency signal processing
  • Knowledge of periodic event characteristics
  • Experience with signal averaging techniques
NEXT STEPS
  • Research optimal window sizes for power spectral density analysis in low-frequency signals
  • Learn about averaging techniques for power spectral density calculations
  • Explore the implications of event duration on spectral analysis
  • Investigate alternative methods for analyzing non-oscillatory periodic signals
USEFUL FOR

Signal processing engineers, researchers in electrical engineering, and anyone involved in analyzing low-frequency periodic events in voltage-time signals.

Dan Kanak
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Hello,
If I wish to measure the power of a very low-frequency periodic event (~.2Hz) in a voltage-time signal what is an ideal window size to use for power spectral analysis. The activity is very short in duration (~30ms) and occurs every 5-10 seconds. My problem is that I need a relatively large number of segments so that I can discard artifactual noise without losing data, but it seems to me that the window size is limited to at least 1/.2Hz. Is this true, or should the window length be at least 30ms. Since the activity isn't really oscillatory but rather periodic discharging, is power spectral analysis even useful in this case? Thanks for your time.

Dan
 
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You have a choice. Average the events and take the PSD of the average. Take the PSD of each and average the answers. At least I think so; I'm rusty at PSD analysis.
 

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