The recursive least-squares (RLS) adaptive filter is an appealing choice in many system
identification problems. The main reason behind its popularity is its fast convergence rate …

Due to its fast convergence rate, the recursive least-squares (RLS) algorithm is very popular
in many applications of adaptive filtering, including system identification scenarios …

This paper proposes a novel augmented space robust adaptive filter by reusing the errors
for online applications. First, a batched augmented space constrained model (ASCM) is …

The auxiliary normal equation is proposed to construct an incremental update (IU) system in
which the increment of weight vector rather than the weight itself is optimized at each …

In this paper, we propose a novel structure for implementing a kernel adaptive filter as an
add-on component for a linear adaptive filter. The kernel adaptive filter has been proposed …

Due to the non-ideal components in the analog front-end of frequency division duplex
transceivers a part of the transmit signal leaks into the receive path. Together with nonlinear …

In this paper, an adaptive adjustment method for the kernel parameter used in the kernel
adaptive filters (KAFs) is proposed. The KAF is one of the linear-in-the-parameters (LIP) …

In this chapter, the family of kernel affine projection algorithms with coherence criterion is
presented. The proportionality principle is translated to the kernel-based version. A new …

In this paper, we consider the characteristics of the kernel adaptive filters for the mixture of
linear and non-linear environments. We first consider employing a linear kernel as one of …

In this paper, a fixed-budget implementation of the kernel proportionate normalized least
mean square (KPNLMS) algorithm using a variable step size scheme is proposed. The …