A new LMS (least-mean-square) adaptive line enhancer algorithm is presented. It makes use of forward and backward prediction errors to update the coefficient values. For a given feedback factor, the algorithm converges to the optimal Wiener solution with the same speed as for the LMS algorithm, but requires about twice the number of multiplications and additions. However, in the situation when the order of the enhancer is at least a few times larger than the number of sinusoids to be enhanced, or when the frequencies of the sinusoids to be enhanced are not close to 0 or 0.5, the misadjustment of the new algorithm is approximately half that of the LMS algorithm.
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