[Scilab-users] Identifying parameters of a multy frequency damped oscillation

[Jens Simon Strom]

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.cormier at 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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