This paper considers the problem of system parameter estimation using adaptive filter.
Conventional adaptive algorithms will result in degraded performance in the presence of …

The monitoring of electrocardiography (ECG) in ambulatory conditions is an important task
for achieving success in remote healthcare monitoring. In this paper, Kalman-based …

Sensor networks are an indispensable part of the Internet of Things (IoT), where sensors
perform data acquisition and information processing tasks to obtain the parameters of …

The convergence rate of the diffusion normalized least mean squares (NLMS) algorithm can
be speeded up by decorrelation of signals. However, the diffusion decorrelation NLMS …

This brief proposes a robust bias-compensated subband adaptive filtering (R-BC-SAF)
algorithm for noisy input and large outliers. We first performs the maximum a posteriori …

Echo seriously damages the speech communication quality of vehicle communication
system and seriously interferes with the normal operation of voice navigation, voice dialing …

This paper considers the scenario of noisy inputs and compressive diffusion (for reducing
communication load) with noisy links over sensor networks. We first study the …

In this letter, we derive a new stepsize adaptation for the normalized least mean square
algorithm (NLMS) by describing the task of linear acoustic echo cancellation from a …

Most active noise control (ANC) algorithms require a model of the secondary path (SP). If
there are large changes in the SP, online SP modeling algorithms may not be able to follow …

Selecting the step of the least mean squares (LMS) algorithm is an old problem. This study
uses a new approach to address this problem resulting in a new algorithm with excellent …