On 8 Jul, 13:13, "sancho-fx1" <sancho-...@gmx.de> wrote:
> Thanks a lot for your response. I will try to wade through your suggestions
> but they sound quite complicated to me.

That's because they are. RBJ is perfectly right in that the
general idea is simple, but that actually doing it is a bit
involved.

> In this respect I've got another question which is related to my first.
> Let's assume I have finally found a set of coefficients for my IIR which
> 'solve' a given problem. If I understood correctly, these coefficient
> values will only be 'correct' for a single sampling rate of the signal.

Correct.

> So
> if someone want to use the filter with a signal of a different sampling
> rate, he need to somehow solve the tasks you described before, right?

Correct.

The thing is that a digital filter is designed in terms of *relative*
frequency
in digital domain. If you want a cut-off at 10 Hz and the sampling
rate is
50 Hz, the relative cut-off frequency is 10/50 = 0.2. If the sampling
frequency is 100 Hz, the cut off at 10 Hz becomes a relative
frequency
of 10/100 = 0.1.

> Now my question would be, if I want to describe the filter properties, for
> example in a publication, how would I do it in a way that is independent of
> the sampling rate I used?

You can't, if you use a discrete-time filter to process a sampled
process. You have to state the sampling rate to convince the readers
of your article that you did a good job. Lots of people become
very sceptical if a system is sampled too close to the Nyquist limit.

> Would it be preferable to publish impulse response plots instead of the
> filter coefficients?

Depends on what you want to express. Lots of people prefer to use
spectrum magnitude plots when describing filters.

Rune