This paper describes a new variant of the least-mean-squares (LMS) algorithm, with low computational complexity, for updating an adaptive lter. The reduction in complexity is obtained by using values of the input data and the output error, quantized to the nearest power of two, to compute the gradient. This eliminates the need for multipliers or shifters in the algorithm's update section. The q...
