Re: using iFFT on a Continuous Time Transfer Function

• To: mathgroup at smc.vnet.net
• Subject: [mg48686] Re: using iFFT on a Continuous Time Transfer Function
• From: "Steve Luttrell" <steve_usenet at _removemefirst_luttrell.org.uk>
• Date: Thu, 10 Jun 2004 02:44:01 -0400 (EDT)
• References: <ca6hrm\$g76\$1@smc.vnet.net>
• Sender: owner-wri-mathgroup at wolfram.com

```You don't say how you sampled your frequency domain function. If you are
getting unexpected results then it is almost certainly because your sampling
rate was too low. For uniformly spaced samples you have to sample at at
least the Nyquist rate.

An alternative approach is to NOT sample the frequency domain function, but
to do an inverse Fourier transform back to the time domain, and then to
sample the result. The same comment as above applies about sampling at at
least Nyquist rate.

Steve Luttrell

"Vin" <car_d_active_unit at hotmail.com> wrote in message
news:ca6hrm\$g76\$1 at smc.vnet.net...
> Hello,
>
> I know what my signal looks like in the frequency domain, because I
> have a analytic expression for that (i.e., a function of frequency). I
> don't have a time domain counterpart though, but I expect it to be a
> real valued pulse-like signal, lasting a few nanoseconds.
>
> I am wondering, can I somehow apply the IFFT to this frequency domain
> function to get a discrete time representation of the time domain
> counterpart?
>
> If so, any hints as to how to go about it?
>
> I have already tried sampling my frequency domain function to produce
> something like the output of a FFT, e.g., with the -ve frequency
> function values being generated from the complex conjugate of the
> positive frequency function values etc. However, when I apply the
> IFFT, I get nothing like what I expect.
>
> thanks for any help
>
> Vin
>

```

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