Unlike traditional homogeneous single-task wireless sensor networks (WSNs),
heterogeneous and multitask WSNs allow the cooperation among multiple heterogeneous …

In this paper, a distributed diffusion unscented Kalman filtering algorithm based on
covariance intersection strategy (DDUKF-CI) is proposed for target tracking with intermittent …

This article presents communication-efficient approaches to federated learning (FL) for
resource-constrained devices with access to streaming data. In particular, we first propose a …

This paper proposes efficient batch-based and online strategies for kernel regression over
graphs (KRG). The proposed algorithms do not require the input signal to be a graph signal …

We address the problem of angle-of-arrival (AOA) target tracking using multiple unmanned
aerial vehicles (UAVs) in three-dimensional (3D) space. A distributed 3D AOA target tracking …

This paper presents adaptive link selection algorithms for distributed estimation and
considers their application to wireless sensor networks and smart grids. In particular …

In this brief, we propose a reduced communication diffusion algorithm for distributed
estimation over multi-agent. In the proposed algorithm, agents cooperatively optimize a …

Many problems in multiagent networks can be solved through distributed learning (state
estimation) of linear dynamical systems. In this paper, we develop a partial-diffusion Kalman …

Online federated learning (FL) enables geographically distributed devices to learn a global
shared model from locally available streaming data. Most online FL literature considers a …

Federated learning (FL) literature typically assumes that each client has a fixed amount of
data, which is unrealistic in many practical applications. Some recent works introduced a …