Reply by Sverre Hestetun April 28, 20052005-04-28
P&#4294967295; 22 Apr 2005 00:47:20 -0700, skrev Gie78 <Markus.Schweikhardt@web.de>:

> Hi > > I have some Problems with the NLMS. I have written a MATLAB skript to > simulate the LMS and NLMS now I will compare these two algorithms. > Especially the convergence speed. Here I will compare the learning > curves. > Inputsignal: White noise (Matlab randn()) > > My major Problem is the choose of the different Parameters like step > size and so on. > > The coefficient-update: w(n+1)=w(n)+mu(n)*e(n)*x(n) > > mu(n)=alpha/(L*P(n)) > > P(n)=(1-beta)*P(n-1)+beta*x(n)*x(n) > > alpha= normalization between 0 and 2 > beta = windowsize for Powerestimation > > So has anybody experience with the NLMS und the choose of the > Parameters?
My best advice is that you experiment with those parameters. For random signals, mu(n) generally should be small. There is also another method that I used: P(n) = 1/L*x(n:-1:n-L+1)*x(n:-1:n-L+1) Sverre
Reply by Gie78 April 22, 20052005-04-22
Hi 

I have some Problems with the NLMS. I have written a MATLAB skript to
simulate the LMS and NLMS now I will compare these two algorithms.
Especially the convergence speed. Here I will compare the learning
curves.
Inputsignal: White noise (Matlab randn())

My major Problem is the choose of the different Parameters like step
size and so on.

The coefficient-update: w(n+1)=w(n)+mu(n)*e(n)*x(n)

mu(n)=alpha/(L*P(n))

P(n)=(1-beta)*P(n-1)+beta*x(n)*x(n)

alpha= normalization between 0 and 2
beta = windowsize for Powerestimation

So has anybody experience with the NLMS und the choose of the
Parameters?

Thanks Markus