analysis:course-w16:week5
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analysis:course-w16:week5 [2016/02/02 14:00] mvdm [Generating and plotting basic sinusoids] |
analysis:course-w16:week5 [2018/07/07 10:19] (current) |
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| (Note that the above is a quick hack of something that should really be implemented in a nice function, because the above commands really correspond to one conceptual operation of decimation, presenting an opportunity for making the code more readable and maintainable. But I haven't gotten around to that yet.) | (Note that the above is a quick hack of something that should really be implemented in a nice function, because the above commands really correspond to one conceptual operation of decimation, presenting an opportunity for making the code more readable and maintainable. But I haven't gotten around to that yet.) | ||
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| + | ☛ Now that you have decimated the data, also update your sampling frequency ''Fs''. | ||
| Now we can compute the spectrum: | Now we can compute the spectrum: | ||
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| {{ :analysis:course:week4_fig7.png?600 |}} | {{ :analysis:course:week4_fig7.png?600 |}} | ||
| - | Note that we are plotting not the raw power spectrum but rather the ''10*log10()'' of it; this is a convention similar to that of the definition of the decibel (dB), the unit of signal power also applied to sound waves. | + | Note that we are plotting not the raw power spectrum but rather the ''10*log10()'' of it; this is a convention similar to that of the definition of the decibel (dB), the unit of signal power also applied to sound waves. The values on your vertical axis may look different, depending on what version of ''LoadCSC()'' was used. |
| Regardless, it doesn't look very good! The estimates look very noisy, a characteristic of the periodogram method. | Regardless, it doesn't look very good! The estimates look very noisy, a characteristic of the periodogram method. | ||
analysis/course-w16/week5.1454439618.txt.gz · Last modified: 2018/07/07 10:19 (external edit)
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