Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
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This paper describes a set of block processing algorithms which contains as extremal cases the Normalized LMS (NLMS) and the block RLS (BRLS) algorithms. These algorithms use small block lengths, thus allowing easy implementation and small input-output delay. It is shown that these algorithms require a lower number of arithmetic operations than the classical Least Mean Square (LMS) algorithm, while converging much faster. A precise evaluation of the arithmetic complexity is provided, and the adaptive behavior of the algorithm is analyzed. Simulations are provided: A first one shows that the tracking characteristics of the new algorithm compared to the NLMS algorithm are also improved. A second one shows that, even in the case where noise is added to the reference signal, the proposed algorithm allows altogether a faster convergence and a lower residual error than the NLMS algorithm.