Abstract
In this paper, we study a modified normalized least mean square (NLMS) algorithm for updating coef-ficients of an adaptive FIR digital filter (ADF). In the modified adaptive algorithm, filter coefficients are updated with NLMS algorithm for each sample, but the coefficients are freezed when the input signal is smaller than a given threshold (constant). This modified NLMS has been known, but not been analyzed.
In this paper, we call the modified NLMS as conditioned NLMS (C-NLMS) and analyze the convergence characteristics. As a result, the optimum threshold value is obtained. The simulation results and theo-retical analyses show the effectiveness of the C-NLMS with the proposed threshold, and a good agreement between both results. The stability of the NLMS algorithm in the presence of small input signal is improved. The convergence speed of the C-NLMS ADF under the noisy circumstances is also faster than that of the unconditioned ordinary NLMS ADF in small tap number case.
