I am a little confused by your ppost.  You seem to be saying that
since the filter is 32 samples long, you are iterating over 32
samples.  But I don't think that's what you mean.  If you are asking
how many samples it will take for the filter to converge, then that is
an exponential exp[-1/(mu  * lambda(m))], where mu is the gain, and
lambda(m) is the minimum eigenvalue.  The number of samples it will
take to converge is dependent on the sampling rate.


Maurice Givens


"Zach R." <zrimkunas@verizon.net> wrote in message news:<yj3Qa.11308$Kw1.8216@nwrdny02.gnilink.net>...
> Hi all,
>   I am currently trying to implement a simple LMS algorithm in C and on an
> analog deviced blackfin ez-kit.  The only real problem is that I am trying
> to implement it in a streaming manner and as close to real time as possible.
> I have an implementation but it isn't working.
>     I am wondering how many samples should I be looking at when estimating
> the gradient?  The books I have been reading pretty much just use the
> samples in the filter e.g. the last 32 samples for a 32nd order filter.
> That is how I have been estimating the gradient, should it work?
> 
> Thanks for your help,
> Zach

It should work. Try playing with the step size. 
If you are doubtful about your implementation of the algorithm try it
in matlab or 'C' code on PC.

Navan

"Zach R." <zrimkunas@verizon.net> wrote in message news:<yj3Qa.11308$Kw1.8216@nwrdny02.gnilink.net>...
> Hi all,
>   I am currently trying to implement a simple LMS algorithm in C and on an
> analog deviced blackfin ez-kit.  The only real problem is that I am trying
> to implement it in a streaming manner and as close to real time as possible.
> I have an implementation but it isn't working.
>     I am wondering how many samples should I be looking at when estimating
> the gradient?  The books I have been reading pretty much just use the
> samples in the filter e.g. the last 32 samples for a 32nd order filter.
> That is how I have been estimating the gradient, should it work?
> 
> Thanks for your help,
> Zach

Hi all,
  I am currently trying to implement a simple LMS algorithm in C and on an
analog deviced blackfin ez-kit.  The only real problem is that I am trying
to implement it in a streaming manner and as close to real time as possible.
I have an implementation but it isn't working.
    I am wondering how many samples should I be looking at when estimating
the gradient?  The books I have been reading pretty much just use the
samples in the filter e.g. the last 32 samples for a 32nd order filter.
That is how I have been estimating the gradient, should it work?

Thanks for your help,
Zach