teilhardo
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Hi,
I have several sets of stochastic signals that oscillate about the x-axis over time. I would like to transform these signals into the frequency domain (make a periodogram) so that I can which signal has the most stable frequency. I was thinking about using taking the Fourier transform of each data set, finding the frequency with the max power, then comparing the power of this frequency to the integral of all the other frequencies with power greater than zero. With my somewhat limited mathematical background, this is all that I could come up with, maybe somebody might know something less complicated and more developed. How would this compare to a short time Fourier transform?
Thanks,
Tei
I have several sets of stochastic signals that oscillate about the x-axis over time. I would like to transform these signals into the frequency domain (make a periodogram) so that I can which signal has the most stable frequency. I was thinking about using taking the Fourier transform of each data set, finding the frequency with the max power, then comparing the power of this frequency to the integral of all the other frequencies with power greater than zero. With my somewhat limited mathematical background, this is all that I could come up with, maybe somebody might know something less complicated and more developed. How would this compare to a short time Fourier transform?
Thanks,
Tei