The optimum scalar data nonlinearity in LMS adaptation for arbitrary IID inputs

The authors show that the optimum nonlinear scale operation upon the elements of the observation vector in the LMS algorithm is exactly x/(1+ mu x/sup 2/) for any independent stochastic data input and any noise density. Moreover, use of such a nonlinearity can yield a significant performance improvement in fast adaptation situations.<
>