FPGA Central

Hi,

I am trying to implement leaky NLMS for adaptive beamforming, but I foun
that the noise reduction performance is worse than that of NLMS. The dat
I used are simulated data, and I assume the noise and speech sources ar
well seperated. Can anybody give me some suggestions about applying leak
NLMS for GSC? Is Leaky really better than that of NLMS?

Thanks a lot!

Best Regards,
Jing

"Jing" <[email protected]> wrote in message
news:[email protected]..
> Hi,
>
> I am trying to implement leaky NLMS for adaptive beamforming, but I found
> that the noise reduction performance is worse than that of NLMS. The data
> I used are simulated data, and I assume the noise and speech sources are
> well seperated. Can anybody give me some suggestions about applying leaky
> NLMS for GSC? Is Leaky really better than that of NLMS?
>
> Thanks a lot!
>
> Best Regards,
> Jing
>
>
>
I suspect that leaky anything won't be as good as pure integrators in an
algorithm. For stationary data NLMS woudl come out on top. Try
non-stationary data - the leaky one may track better.


Naebad

Jing wrote:

> Hi,
>
> I am trying to implement leaky NLMS for adaptive beamforming, but I found
> that the noise reduction performance is worse than that of NLMS.


Yes, this is what expected.

> The data
> I used are simulated data, and I assume the noise and speech sources are
> well seperated. Can anybody give me some suggestions about applying leaky
> NLMS for GSC? Is Leaky really better than that of NLMS?
>

It depends. The amount of leak is the tradeoff between the stability and
the accuracy. You should optimize it for your application.



Vladimir Vassilevsky

DSP and Mixed Signal Design Consultant

http://www.abvolt.com

Jing wrote:
> Hi,
>
> I am trying to implement leaky NLMS for adaptive beamforming, but I found
> that the noise reduction performance is worse than that of NLMS. The data
> I used are simulated data, and I assume the noise and speech sources are
> well seperated. Can anybody give me some suggestions about applying leaky
> NLMS for GSC? Is Leaky really better than that of NLMS?

Leaking will always make the adaption accuracy poorer than not leaking.
Think about it - you keep shrinking the coefficients, so the adaption is
always fighting to reach its target. It never quite gets there.

Leaking is a way to stop coefficients wandering off to extreme values.
This can happen at places where the signal is always close to zero
(think of things like the mid-point between symbols in a channel
equalizer). No matter how far off the coefficient wanders
big_coeff*tiny_signal is always very small, and never coaxed the
wandering coefficient back towards zero.

If you face wandering coefficients, leaking is a huge benefit. If you
don't, leaking is a looser. The level of leaking you should use is a
compromise between stopping the coefficient wandering (big leak is
better) and avoiding detuning of the adaption (small leak is better).

Regards,
Steve