[Numpy-discussion] custom Welch method for power spectral density

[Robert Kern]

On Fri, Jan 12, 2018 at 1:12 PM, Seb <spluque at gmail.com> wrote:
>
> Hello,
>
> I'm trying to compute a power spectral density of a signal, using the
> Welch method, in the broad sense; i.e. splitting the signal into
> segments for deriving smoother spectra.  This is well implemented in
> scipy.signal.welch.  However, I'd like to use exponentially increasing
> (power 2) segment length to dampen increasing variance in spectra at
> higher frequencies.  Before hacking the scipy.signal.spectral module for
> this, I'd appreciate any tips on available packages/modules that allow
> for this kind of binning scheme, or other suggestions.

Not entirely sure about this kind of binning scheme per se, but you may
want to look at multitaper spectral estimation methods. The Welch method
can be viewed as a poor-man's multitaper. Multitaper methods give you
better control over the resolution/variance tradeoff that may help with
your problem. Googling for "python multitaper" gives you several options; I
haven't used any of them in anger, so I don't have a single recommendation
for you. The nitime documentation provides more information about
multitaper methods that may be useful to you:

http://nipy.org/nitime/examples/multi_taper_spectral_estimation.html

--
Robert Kern
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