filtering out harmonic trend
Matthias Brennwald
matthias at brennwald.org
Tue Dec 4 13:10:09 CST 2007
On 04.12.2007, at 14:41, help-octave-request at octave.org wrote:
> Message: 8
> Date: Tue, 04 Dec 2007 13:39:22 +0100
> From: Francesco Potorti` <Potorti at isti.cnr.it>
> Subject: filtering out harmonic trend
> To: Octave users list <help-octave at bevo.che.wisc.edu>
> Message-ID: <E1IzX3a-0003G2-90 at tucano.isti.cnr.it>
> Content-Type: text/plain; charset=iso-8859-1
>
> I have a 200,000 samples measurement, which is a sort of noise with
> bandwidth in the order of the inverse of 500 samples. Superimposed to
> this noise there is a very slow sinusoid with a period of about
> 300,000
> samples. This means that my measurements do not even see a complete
> cycle of this sinusoid.
>
> I want to estimate the sinusoid (in order to remove it from the
> measurement). So I need some sort of very-low pass filter. However,
> usign a simple causal low-pass filter would give me a delayed output.
> Can anyone suggest some keyword for a noncausal filter to look for? I
> guess that it could be simple, because the bandwidths of signal and
> noise are so far away each other.
If the low-frequency signal is a 'clean' sinusoid, then I'd try
fitting a sinusoid to the data, and then subtract this sinusoid from
the data. If the sinusoid is a function of time t and of the form s
(t) = A * sin(2*pi*f*t+phi), then the fit parameters would be A, f,
and phi. You can use fmins (available in the optim package) to find
the best-fit values for A, f, and phi by minimizing the squared
difference of your data and s(t).
>
> --
> Francesco Potort? (ricercatore) Voice: +39 050 315 3058 (op.
> 2111)
> ISTI - Area della ricerca CNR Fax: +39 050 315 2040
> via G. Moruzzi 1, I-56124 Pisa Email: Potorti at isti.cnr.it
> Web: http://fly.isti.cnr.it/ Key: fly.isti.cnr.it/
> public.key
-------
Matthias Brennwald
Lägernstrasse 6
CH 8037 Zürich
+41 (0)44 364 17 03
matthias at brennwald.org
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