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

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 …

Distributed estimation strategies over wireless sensor networks are one of the active areas
of research due to the wide range of applications in a variety of fields ranging from …

This article proposes diffusion LMS strategies for distributed estimation over adaptive
networks that are able to exploit sparsity in the underlying system model. The approach …

In this paper, we investigate the self-organization and cognitive abilities of adaptive
networks when the individual agents are allowed to move in pursuit of a target. The nodes …

In this paper, the problem of adaptive distributed learning in diffusion networks is
considered. The algorithms are developed within the convex set theoretic framework. More …

In the case where the measurement noise involves impulsive interference, distributed
estimation algorithms based on the mean-square error (MSE) criterion may suffer from …

This work proposes diffusion normalized least mean M-estimate algorithm based on the
modified Huber function, which can equip distributed networks with robust learning …

This work develops robust diffusion recursive least-squares algorithms to mitigate the
performance degradation often experienced in networks of agents in the presence of …

In this correspondence, we analyze the effects of noisy links on the steady-state
performance of diffusion least-mean-square (LMS) adaptive networks. Using the established …