ANALYSIS OF LMS-NEWTON ADAPTIVE FILTERING ALGORITHMS WITH VARIABLE CONVERGENCE FACTOR

An analysis of two LMS-Newton adaptive filtering algorithms with varia ble convergence factor is presented. The relations of these algorithms with the conventional recursive least-squares algorithm are first add ressed. Their performance in stationary and nonstationary environments is then studied and closed-form formulas for the excess mean-square e rror (MSE) are derived. The paper deals, in addition, with the effects of roundoff errors for the case of fixed-point arithmetic. Specifical ly, closed-form formulas far the excess MSE caused by quantization are obtained. The paper concludes with experimental results that demonstr ate the validity of the analysis presented.