Modified LMS algorithm for unbiased impulse response estimation in nonstationary noise

In the presence of input interference, the Wiener solution for impulse resp onse estimation is biased. It is proved that bias removal can be achieved b y proper scaling of the optimal filter coefficients and a modified least me an squares (LMS) algorithm is then developed for accurate system identifica tion in noise. Simulation results show that the proposed method outperforms two total least squares (TLS) based adaptive algorithms under nonstationar y interference conditions.