In article <1991Oct28.051227.4611 at frodo.cc.flinders.edu.au>
>We wish to assess the power of 40Hz activity in short period (100-200msec)
>EEG records sampled at 1khz. The only spectral analysis tool available to
>us is FFT based power spectrum calculation. I'm not at all confident
>that this is the best approach, but have no way to assess this. Could
>anyone *please* help us out ? I guess what I'm asking is whether
>there exists a technique for measuring the power in a limited band, given
>a restricted number of samples ?
>-----------------------------------------------------------------------
> _--_|\ James Tizard
The "maximum entropy" methods works wonders with short samples. It is
outstanding at picking out key frequencies, but one shouldn't put too much
stock in its exact values for power. In contrast, the FFT methods tend to
be better at broad-band power and show broader features in their spectral
estimates. The maximum entropy method basically is done as follows, with
a fair number of variations on the theme used by various people:
Take the autocorrelation of your time series.
Do a (least squares) fit to the autocorrelation of an autoregressive random
process. You will definitely not need an AR process higher than order 30,
perhaps order 10 or 15 will suffice -- you can try it for various orders.
Now plug into the formula for the spectrum of an AR process -- you just
found the AR coefficients in the previous step.
Talk to people in signal processing (that's in electrical engineering). They
spend their life solving the kinds of problems you present.
Stephen Jascourt
