The diffusion LMS algorithm has been extensively studied in recent years. This efficient
strategy allows to address distributed optimization problems over networks in the case …

We consider a network of sensors in which each node may collect noisy linear
measurements of some unknown parameter. In this context, we study a distributed …

The recursive least-squares (RLS) algorithm has well-documented merits for reducing
complexity and storage requirements, when it comes to online estimation of stationary …

This paper presents an efficient adaptive combination strategy for the distributed estimation
problem over diffusion networks in order to improve robustness against the spatial variation …

In this paper, a sparsity promoting adaptive algorithm for distributed learning in diffusion
networks is developed. The algorithm follows the set-theoretic estimation rationale. At each …

We study the problem of distributed least-squares estimation over ad hoc adaptive networks,
where the nodes have a common objective to estimate and track a parameter vector. We …

A distributed least-squares estimation strategy is developed by appealing to collaboration
techniques that exploit the space-time structure of the data, achieving an exact recursive …

Adaptive networks (AN) have been recently proposed to address distributed estimation
problems [1]-[4]. Here we extend prior work to changing topologies and data-normalized …

An adaptive distributed estimation strategy is developed based on incremental gradient
techniques. The proposed scheme addresses the problem of distributed linear estimation in …

A new distributed algorithm for cooperative estimation of a slowly time-varying signal using a
wireless sensor network is presented. The estimate in each node is based on a so called …