Timeline for How can I get the power spectrum density and separate low and high frequencies?
Current License: CC BY-SA 4.0
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| Dec 3, 2021 at 13:02 | history | bumped | CommunityBot | This question has answers that may be good or bad; the system has marked it active so that they can be reviewed. | |
| Nov 3, 2021 at 12:13 | answer | added | Hugh | timeline score: 1 | |
| Nov 2, 2021 at 22:00 | comment | added | flinty |
Get your data as a TimeSeries ts = TimeSeries@Transpose[{0.1*Range[0, Length[data] - 1], data}];, then use PowerSpectralDensity[ts, w] if that's what you mean by spectrum density, or you could use Periodogram[data, SampleRate -> 10] and PeriodogramArray[data, SampleRate -> 10]. This has been asked a number of times before on this site. You'll need more data to get meaningful values: 27 samples is quite low.
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| Nov 2, 2021 at 21:52 | history | edited | flinty | CC BY-SA 4.0 |
added 18 characters in body
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| Nov 2, 2021 at 17:37 | history | asked | Zarabu | CC BY-SA 4.0 |