Abstract
Presents a study of the quantization effects in the finite precision LMS algorithm with power-of-two step sizes. Deterministic nonlinear recursions are presented for the mean and second-moment matrix of the weight vector about the Wiener weight for white Gaussian data models and small algorithm step size /spl mu/. The numerical solutions of these recursions are shown to agree very closely with the Monte Carlo simulations during all phases of the adaptation process. Design examples demonstrate the selection of the number of quantizer bits and the adaptation step size /spl mu/ to yield a desired transient behavior and cancellation performance. The results obtained indicate that previous models are too conservative in predicting the converged MSE for a given number of bits.
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