andrea wrote:
> is there a way to decimate a signal (reduce sampling rate) reducing
> aliasing without implementing a computationally intensive low-pass
> filter?
> Consider that this signal is supposed to have frequency components
> higher than the reduced sampling rate.

If the frequency components higher than half the reduced sampling
are completely characterized, you might be able to subtract or
otherwise account for them after decimation without low-pass
filtering.

e.g. you could implement a computationally intensive high-pass
filter instead, decimate the original and the high band component,
then subtract.  This might actually be useful if the there is something
known about the high band component that makes it easier to filter.

Or perhaps the low band signal of interest does not overlap
with the aliased image of the high band component. In that case
you might not even need to subtract the interference after
decimating.


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

"andrea" <andrea.zonca@gmail.com> wrote in message 
news:1141046701.724840.137370@i40g2000cwc.googlegroups.com...
> Hi,
> is there a way to decimate a signal (reduce sampling rate) reducing
> aliasing without implementing a computationally intensive low-pass
> filter?
> Consider that this signal is supposed to have frequency components
> higher than the reduced sampling rate.
> thanks
>

I guess you mean, "this signal is known to have frequency components higher 
than 1/2 the reduced sampling rate"  Note the "1/2".

Can you decimate, with "reduced" aliasing without computational intensive 
operations?

The question, and thus the answer, is a matter of degree.

A) You can decimate with no filtering and get aliasing.  This may be 
acceptable in some circumstances.

B) You can prefilter simply and get less aliasing than in (A) above.  This 
may be acceptable in some circumstances.

C) You can prefilter better and get even less aliasing than in (B).

D) You can prefilter as best one could and still get aliasing that's 
noticeble in some circumstances.

So, the logical answer to your question is Yes.  You can decimate with 
reduced aliasing without computational intensive operations by using a 
less-than "intensive" filter.

Fred

If your signal is narrowband than you can use a Hilbert transform (if
your signal is real, this will reduce redundancy in the spectrum) and
sample it at twice it's bandwidth (***as opposed to twice the highest
frequency***). The reconstruction is  a little more tricky but still
possible.

Sure... use an analog lowpass filter ahead of the sampler.  You have
just exchanged computational load for circuit complexity - not a bad
tradeoff in some applications.

BR,
Dan

Hi,
is there a way to decimate a signal (reduce sampling rate) reducing
aliasing without implementing a computationally intensive low-pass
filter?
Consider that this signal is supposed to have frequency components
higher than the reduced sampling rate.
thanks