[PD] fft -> get to know of requested frequency range
Lex Ein
lex_ein at f-m.fm
Fri Jul 23 18:22:03 CEST 2004
bp~ has an annoying shelf, which allows significant leakage of
low frequencies which are not of interest.
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For a true bandpass, may I suggest a higher order lowpass and
highpass in combination. From IEMLIB, lp10 and hp10 work well
to form a high-slope bandpass, as in this example patch.
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IOhannes m zmoelnig wrote:
> Christian Klotz wrote:
>
> >
> > On 23.07.2004, at 13:17, IOhannes m zmoelnig wrote:
> >
> >
> > I am new to sound analysis and started using fft because I thought
> > about doing some other things with the sound analysis later. My
> > problem is - even after reading the fft documentation - that I dont
> > know how to handle the real and imaginary data. The main question
> > for me is which objects or arguments have to be set to check if the
> > sound contains the requestd frequency range.
>
>
> probably try [bp~ 11000 100] (see help-patch for [bp~]; play with q)
> then use [env~] to measure the power in the filtered signal. most
> probably you will have to set the result into relation to the
> original signal somehow (to make it robust against loudness variance)
>
>
> as for real and imaginary data: c=x+i*y |c| = sqrt(x2+y2) now x and
> y are your signals; you most likely can skip the sqrt() as it is
> costy and only "scales" (non-linearily) the result.
>
>
> mfg.a.sdr IOhannes
>
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IOhannes m zmoelnig wrote:
> Christian Klotz wrote:
>
>>
>> On 23.07.2004, at 13:17, IOhannes m zmoelnig wrote:
>>
>>
>> I am new to sound analysis and started using fft because I thought
>> about doing some other things with the sound analysis later. My
>> problem is - even after reading the fft documentation - that I dont
>> know how to handle the real and imaginary data. The main question for
>> me is which objects or arguments have to be set to check if the sound
>> contains the requestd frequency range.
>
>
> probably try [bp~ 11000 100] (see help-patch for [bp~]; play with q)
> then use [env~] to measure the power in the filtered signal.
> most probably you will have to set the result into relation to the
> original signal somehow (to make it robust against loudness variance)
>
> as for real and imaginary data:
> c=x+i*y
> |c| = sqrt(x^2+y^2)
> now x and y are your signals; you most likely can skip the sqrt() as
> it is costy and only "scales" (non-linearily) the result.
>
>
> mfg.a.sdr
> IOhannes
>
> _______________________________________________
> PD-list mailing list
> PD-list at iem.at
> to manage your subscription (including un-subscription) see
> http://iem.at/cgi-bin/mailman/listinfo/pd-list
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