This work deals with the topic of information processing over graphs. The presentation is
largely self-contained and covers results that relate to the analysis and design of multi-agent …

Nature provides splendid examples of real-time learning and adaptation behavior that
emerges from highly localized interactions among agents of limited capabilities. For …

Adaptive networks are well-suited to perform decentralized information processing and
optimization tasks and to model various types of self-organized and complex behavior …

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

In this work, we study the task of distributed optimization over a network of learners in which
each learner possesses a convex cost function, a set of affine equality constraints, and a set …

We study the problem of distributed estimation over adaptive networks where
communication delays exist between nodes. In particular, we investigate the diffusion Least …

Recently, the diffusion moving-average (D-MA) scheme has been proposed as a way to
combat noisy links over adaptive networks. However, the current theoretical results focus on …

This paper analyzes the implementation of least-mean-squares (LMS)-based, adaptive
diffusion algorithms over networks in the frequency-domain (FD). We focus on a scenario of …

This paper proposes a distributed estimation technique utilizing the diffusion least mean-
square (LMS) algorithm, specifically designed for sparse systems in which many coefficients …

There has been considerable development of distributed adaptive algorithms in recent years
with diffusion algorithms offering very attractive features, but their performance analysis has …