Combination approaches provide an interesting way to improve adaptive filter performance.
In this paper, we study the mean-square performance of a convex combination of two …

Adaptive filters are at the core of many signal processing applications, ranging from acoustic
noise supression to echo cancelation [1], array beamforming [2], channel equalization [3], to …

This paper studies the statistical behavior of an affine combination of the outputs of two least
mean-square (LMS) adaptive filters that simultaneously adapt using the same white …

Enormous amounts of dynamic observation and measurement data are collected from
sensors in Wireless Sensor Networks (WSNs) for the Internet of Things (IoT) applications …

This brief proposes a combined-step-size (CSS) affine projection sign algorithm (APSA) to
improve the poor tracking capability of the conventional variable-step-size APSA. To achieve …

Large volumes of real-world observation and measurement data are collected from sensory
devices in the Internet of Things (IoT) networks. IoT data is often generated in highly …

As is well known, Hessian-based adaptive filters (such as the recursive-least squares
algorithm (RLS) for supervised adaptive filtering, or the Shalvi-Weinstein algorithm (SWA) for …

Among all adaptive filtering algorithms, Widrow and Hoff's least mean square (LMS) has
probably become the most popular because of its robustness, good tracking properties and …

Adaptive filtering schemes are subject to different tradeoffs regarding their steady-state
misadjustment, speed of convergence, and tracking performance. To alleviate these …

For least mean-square (LMS) algorithm applications, it is important to improve the speed of
convergence vs the residual error trade-off imposed by the selection of a certain value for …