ARMA is very much based on stochastics. I don't see this relevant here.
Regards
Jens
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Am 07.09.2015 16:18, schrieb roger.corm...@ncf.ca:
Would you consider an ARMA model of the signal? You need to chose the order of
the system so a bit of experimenting is needed. Just an idea.
Regards,
Roger.
___________________________
Dr. Roger Cormier, P.Eng.
Home Tel. & Fax: 613-823-7299
Le lun. 7 sept. 2015 à 08:26, Jens Simon Strom a écrit :
Hi Scilab users,
I want to analyse a microphone recording of the sound of a bell or gong. Given
ia the equidistantly sampled sound pressure y(t) after a stroke for 10 s
.
The ansatz
y=sum( A_i*exp(-d_i*t))*cos(2*%pi*f_i+alpha_i) )
for i=1,2,...5 or more
is assumed to approximate the signal where A_i, d_i, f_i, and alpha_i are the
unknown amplitudes, danping factors, frequencies, and phase angles of y. The
analysis may be restricted to the lowest 5 frequencies fi.
Does Scilab offer a method for this? FFT seems not to be adequate because the
signal is aperiodic (silence after 10 s).
Is nonlinear regression (with which I'm fmiliar) a promising way. The lowest
frequencies can probably be concluded from a short time DFT where damping is
negligible.
Kind regards
Jens
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