On Fri, 4 Feb 2022 at 10:41, Jack Hickish <jackhick...@gmail.com> wrote:

>
>
> On Fri, 4 Feb 2022 at 07:08, Morag Brown <mbr...@sarao.ac.za> wrote:
>
>> Hey Nikhail,
>>
>> The FFT is a Hermitian function, which means that it has the property:
>>
>> [image: Screenshot from 2022-02-04 08-34-24.png]
>>
>> This principle is used in the real wideband FFT to compute 2 real FFTs
>> using one complex FFT core - this
>> <http://www.hyperdynelabs.com/dspdude/papers/COMPUTING%20THE%20FFT%20OF%20TWO%20REAL%20SIGNALS%20USING%20A%20SINGLE%20FFT.pdf>
>>  paper
>> explains it well. For a detailed explanation on how the CASPER FFT works
>> specifically, Ryan Monroe's paper on Improving the Performance and Resource
>> Utilization of the CASPER FFT and Polyphase FIlterbank goes into quite a
>> lot of detail.
>>
>>
> Hi Mikhil, Morag,
>

Evidently it's contagious. Sorry Nikhil!


>
>> You only get 32 output channels because the CASPER wideband FFT discards
>> all negative frequency components as they're just a mirror of positive
>> frequency components and aren't needed.
>>
>
> This is completely right, but to address the subtlety Mikhil raised about
> N/2 vs N/2+1 chans --
>
> The CASPER FFT doesn't give you the "last" FFT bin (the one whose edge is
> at the Nyquist frequency). This bin, like the DC bin, contains real-valued
> output for real-valued input (since the DC bin coefficients are all 1 and
> the Nyquist bin coefficients are +/-1), so I think the CASPER FFT could use
> the DC bin that it does output to encode both the DC and Nyquist bin
> contents (one in the real part, one in the imag). I'm fairly sure the
> CASPER FFT doesn't do this but I also vaguely recall this coming up in
> conversation before. I think the issue is not that the FFT internals don't
> compute the relevant numbers but is simply that outputting N/2+1 channels
> would lead to an annoying input:output data ratio.
>
> Cheers
> Jack
>
>
>> Morag
>>
>> On Fri, Feb 4, 2022 at 7:10 AM Nikhil Mahajan <maha...@astro.utoronto.ca>
>> wrote:
>>
>>> Dear CASPERites,
>>>
>>> I am a graduate student at the University of Toronto (working with
>>> Marten van Kerkwijk) and I have some raw baseband data collected using
>>> PUPPI (Arecibo) - and I am on a quest to invert the polyphase filter bank.
>>> I have 32 channels of complex-baseband that I would very much like to
>>> combine into a single 100 MHz bandwidth stream.
>>>
>>> To do this, I would need to understand some of the specifics of the
>>> filter bank pipeline (so that I can successfully invert each step). This is
>>> my current understanding of what happened to the data I have:
>>>
>>> 1. Real-valued data sampled at 200 MS/s arrives at the Casper BEE2 board.
>>> 2. This goes through a real-input PFB implementation such as
>>> `pfb_fir_real` and using a 12-tap, 64-branch polyphase filter (I have the
>>> filter coefficients that were used here). This step outputs 64 streams of
>>> real-valued data.
>>> 3. Then, for the DFT step of the filterbank, the 64 real-valued streams
>>> are passed through the `fft_wideband_real` block to get 32 channels of
>>> complex-valued data.
>>> 4. This is then saved to disk.
>>>
>>> (I hope someone familiar with PUPPI can correct me here if I am wrong
>>> about any of the above)
>>>
>>> Step 3 is the step I am confused about. `fft_wideband_real` does not
>>> appear to be a conventional real-input N-point FFT implementation (Else I
>>> would have N/2 + 1 channels instead of just N/2). Some documentation on
>>> this block says that it "computes the real-sampled Fast Fourier
>>> Transform using the standard Hermitian conjugation trick". What is this
>>> standard Hermitian conjugation trick? I am totally unfamiliar with this.
>>> Would I be wrong in guessing it uses some sort of trick to convert 64 real
>>> numbers to 32 complex numbers and then applies a regular ol' complex-valued
>>> FFT on them?
>>>
>>> Thank you so much! I appreciate any and all guidance this mailing list
>>> can provide.
>>>
>>> Cheers,
>>> Nikhil Mahajan
>>>
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>> .
>>
>

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