This paper surveys recent advances related to adaptation, learning, and optimization over
networks. Various distributed strategies are discussed that enable a collection of networked …

In recent years, a compelling need has arisen to understand the effects of distributed
information structures on estimation and filtering. In this study, a bibliographical review on …

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 …

We consider the problem of distributed estimation, where a set of nodes is required to
collectively estimate some parameter of interest from noisy measurements. The problem is …

We study the problem of distributed Kalman filtering and smoothing, where a set of nodes is
required to estimate the state of a linear dynamic system from in a collaborative manner. Our …

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

This paper is concerned with a new distributed H∞-consensus filtering problem over a finite-
horizon for sensor networks with multiple missing measurements. The so-called H∞ …

Distributed multi-target tracking (DMTT) is addressed for sensors having different fields of
view (FoVs). The proposed approach is based on the idea of fusing the posterior Probability …

In this paper, the distributed H∞ filtering problem is addressed for a class of polynomial
nonlinear stochastic systems in sensor networks. For a Lyapunov function candidate whose …

In this paper, the partial-information-based (PIB) distributed filtering problem is addressed
for two-targets tracking sensor networks. Different from existing distributed filters, the …