We propose a recursive constrained least lncosh (RCLL) adaptive algorithm to combat the
impulsive noises. In general, the lncosh function is used to develop a new algorithm within …

Constrained adaptive filtering algorithms have been extensively studied in many
applications. Most existing constrained adaptive filtering algorithms are developed under the …

We propose a constrained least lncosh (CLL) adaptive filtering algorithm, which, as we
show, provides better performance than other algorithms in impulsive noise environment …

Minimum error entropy (MEE), as a robust adaption criterion, has received considerable
attention due to its broad applicability, especially in the presence of non-Gaussian noises. In …

This brief proposed a constrained-Rényi kernel functioned (CqRKF) adaptive algorithm,
which used new cost function created by-Rényi kernel function within the solution of …

The goal of this paper is to derive a novel online algorithm for classification in reproducing
kernel hilbert spaces (RKHS) by exploiting projection-based adaptive filtering tools. The …

In many applications, the constrained adaptive filtering algorithm has been widely studied.
The classical constrained LMS algorithm is widely used because of its low computational …

Thanks to the ability of preventing the accumulation of errors, constrained adaptive filtering
(CAF) algorithms have been widely applied. However, in practice, non-Gaussian noise may …

Most of the existing distributed adaptive filtering algorithms over wireless sensor networks
(WSNs) are developed, aiming to solve unconstrained network optimization problems …

Recently, the constrained adaptive filtering algorithms with strong robustness to non-
Gaussian noise have been widely studied. Among them, the robust constrained least mean …