In this brief, an affine-projection-like M-estimate (APLM) algorithm is proposed for robust
adaptive filtering. To eliminate the adverse effects of impulsive noise in case of the impulse …

This paper proposes two gradient-based adaptive algorithms, called the least mean M
estimate and the transform domain least mean M-estimate (TLMM) algorithms, for robust …

This paper proposes a recursive least M-estimate (RLM) algorithm for robust adaptive
filtering in impulse noise. It employs an M-estimate cost function, which is able to suppress …

This paper studies the problem of robust adaptive filtering in impulsive noise environment
using a recursive least M-estimate algorithm (RLM). The RLM algorithm minimizes a robust …

An M-estimate adaptive filter for robust adaptive filtering in impulse noise is proposed.
Instead of using the conventional least-square cost function, a new cost function based on …

This letter proposes a set‐membership normalised least M‐estimate algorithm based on
Wiener spline adaptive filter (SAF). The proposed algorithm combines the set‐membership …

The errors-in-variables (EIV) model is widely used in linear systems where both input and
output signals are contaminated with noise. For the parameter estimation in the EIV model …

Using the generalized Gaussian probability density function as the kernel, a generalized
correntropy has been proposed. A generalized maximum correntropy criterion (GMCC) …

We propose an affine projection M-estimate subband adaptive filter (APM-SAF), which is
characterized by its robustness against impulsive noise. Instead of the conventional mean …

We proposed a Lawson-norm-based adaptive estimation algorithm within the affine-project
theory framework and give a name of Lawson-norm adaptive filter (LNAF) algorithm. The …