A Nonparametric VSS NLMS Algorithm

TLDR

Numerous VSS‑NLMS algorithms exist, but many rely on hard‑to‑tune parameters that compromise reliability. The letter aims to (1) present a simple derivation of VSS‑NLMS algorithms and (2) propose a new nonparametric VSS‑NLMS that is easy to control and performs well in acoustic echo cancellation. The authors derive VSS‑NLMS‑type algorithms in a straightforward manner and introduce a nonparametric variant that requires minimal parameter tuning and achieves good performance in acoustic echo cancellation.

Abstract

The aim of a variable step size normalized least-mean-square (VSS-NLMS) algorithm is to try to solve the conflicting requirement of fast convergence and low misadjustment of the NLMS algorithm. Numerous VSS-NLMS algorithms can be found in the literature with a common point for most of them: they may not work very reliably since they depend on several parameters that are not simple to tune in practice. The objective of this letter is twofold. First, we explain a simple and elegant way to derive VSS-NLMS-type algorithms. Second, a new nonparametric VSS-NLMS is proposed that is easy to control and gives good performances in the context of acoustic echo cancellation