This article studies the mean and mean-square behaviors of the M-estimate based
normalized subband adaptive filter algorithm (M-NSAF) with robustness against impulsive …

In this paper, three Lorentzian based robust adaptive algorithms are proposed for identifying
systems in presence of impulsive noise. The first algorithm called Lorentzian adaptive …

Sparse recursive least squares (RLS) adaptive filter algorithms achieve faster convergence
and better performance than the standard RLS algorithm under sparse systems. Existing …

This paper presents a family of robust set-membership normalized subband adaptive
filtering (RSM-NSAF) algorithms for acoustic echo cancellation (AEC). By using a new robust …

In this paper, we introduce a new approach to deadlock-free routing in wormhole-routed
networks called the message flow model. This method may be used to develop …

In this paper, we propose a novel normalized subband adaptive filter algorithm suited for
sparse scenarios, which combines the proportionate and sparsity-aware mechanisms. The …

Proportionate-type adaptive filtering (PtAF) algorithms have been successfully applied to
sparse system identification. The major drawback of the traditional PtAF algorithms based on …

The proportionate updating (PU) and zero-attracting (ZA) mechanisms have been applied
independently in the development of sparsity-aware recursive least squares (RLS) …

In this paper, an enhanced proportionate normalized least mean square (PNLMS) algorithm
with the hybrid l 2, 0-norm constraint is proposed for block-sparse signal processing. The …

For adaptive echo cancellation in hands-free communication systems, a family of bias-
compensated sparsityaware normalized least mean M-estimate (NLMM) algorithms is …