We study the problem of distributed detection, where a set of nodes is required to decide
between two hypotheses based on available measurements. We seek fully distributed and …

We deal with distributed estimation of deterministic vector parameters using ad hoc wireless
sensor networks (WSNs). We cast the decentralized estimation problem as the solution of …

Adaptive algorithms based on in-network processing of distributed observations are well-
motivated for online parameter estimation and tracking of (non) stationary signals using ad …

Distributed estimation over networks has received a lot of attention due to its broad
applicability. In diffusion type of distributed estimation, the parameters of interest can be well …

This brief proposes a robust distributed estimation algorithm in presence of impulsive noise.
Impulsive noises are present both in the measurements and in the communication links in a …

In this work, we analyze the mean-square performance of different strategies for distributed
estimation over least-mean-squares (LMS) adaptive networks. The results highlight some …

A distributed estimation algorithm for sensor networks is proposed. A noisy time-varying
signal is jointly tracked by a network of sensor nodes, in which each node computes its …

Recursive least-squares (RLS) schemes are of paramount importance for reducing
complexity and memory requirements in estimating stationary signals as well as for tracking …

Wireless sensor networks are capable of collecting an enormous amount of data over space
and time. Often, the ultimate objective is to derive an estimate of a parameter or function from …

We formulate and study distributed estimation algorithms based on diffusion protocols to
implement cooperation among individual adaptive nodes. The individual nodes are …