Re: adaptive filtering

[Julius Smith]

It sounds to me like you want an adaptive "moving average" filter that slides along and adjusts its length so as to include five or so spikes under the running convolution.  I would probably do this in two passes, the first pass logging where the spikes are, and the second pass applying the time-varying FIR smoothing filter. The Goetzel algorithm could provide an efficient varying FIR implementation for the "boxcar" case, especially in an .oct file. - jos

At 05:51 AM 1/21/2009, Andreas Romeyke wrote:

Hello,

Am Wed, 21 Jan 2009 10:31:28 +0100
schrieb "frederic manseau" <address@hidden>:

> I would like to smooth the distribution of these PSTH using an
> "adaptive filter" (which I think should be centered on each time step
> and widened to capture something like 5-10 spikes)
>
> Does anyone have any idea of how to do that with Octave ?
>

Please have a look at http://sccn.ucsd.edu/eeglab/. Eeglab is a free
toolbox to handle such tasks. Please do not hesitate to ask your
question on the EEGLab-Mailinglist. a whole bunch of eeglab functions
are near compatible with Octave 3.xx (see Testsuite at
https://svnserv.cbs.mpg.de/eeglab/ for details).

Bye Andreas

--
Software Developer / Dipl. Inform. (FH)
Max Planck Institute for Human Cognitive and Brain Sciences
Department of Psychology
Stephanstr. 1a, 04103 Leipzig, Germany



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Julius O. Smith III <address@hidden>
Prof. of Music and Assoc. Prof. (by courtesy) of Electrical Engineering
CCRMA, Stanford University
http://ccrma.stanford.edu/~jos/