Re: Interpolation using polyphase FIR filter: Finding coeffisients

On Oct 4, 2:04 am, "MrAlfred" <jonne...@xxxxxxxxx> wrote:
Ron N wrote:
The problem is that filter coefficients *can* be found from this
information, an infinite number of sets of coefficients, including
just 1.0 (duplicate the nearest sample). If 1.0 isn't good enough,
why not? If 1.0 isn't good enough, then you must have some
unstated lower bound on interpolation accuracy.

I thought duplicating the nearest sample would give unwanted repeating
specters?? If not, 1.0 is probably what I want.

Yes, duplicating samples will create spectral aliasing.

For some metrics, the "quality" of a filter will increase with the
number of coefficients, without bound. Where do you stop if
you don't want to filter infinitely? If you don't want an infinite
FIR computation, then you must have some unstated upper
bound of quality of interpolation. Some number of bits of
precision or something.

I really don't know the answer to this one. I want the signal to be "the
same as before interpolating" and with no repeating specters. If 1.0 isn't
good enough, what about 10 or 20 sets of coeffisients? Would i.e 30 sets of
coeffisients work fine for most applications, or does it not work that way?

The problem is that any finite length FIR will also leave
spectral aliases; just smaller amounts as the FIR length
increases and the coefficients improve. The number of sets
depends on the requirements of your application, as every
application may have a different requirement for how small the
spectral images have to become before one can safely ignore
them (for instance if they are smaller than some quantization
error, the thermal noise in the original signal, or the amount
needed to demodulate some data in the signal, etc.)


IMHO. YMMV.
--
rhn A.T nicholson d.0.t C-o-M

.

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