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From: | Matthias Brennwald |
Subject: | Re: filtering out harmonic trend |
Date: | Tue, 4 Dec 2007 20:10:09 +0100 |
On 04.12.2007, at 14:41, address@hidden wrote:
Message: 8 Date: Tue, 04 Dec 2007 13:39:22 +0100 From: Francesco Potorti` <address@hidden> Subject: filtering out harmonic trend To: Octave users list <address@hidden> Message-ID: <address@hidden> 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 tothis noise there is a very slow sinusoid with a period of about 300,000samples. 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: address@hiddenWeb: 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 address@hidden
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