Recent advances in wired and wireless technology lead to the emergence of large-scale
networks such as Internet, wireless mobile ad-hoc networks, swarm robotics, smart-grid, and …

We apply diffusion strategies to develop a fully-distributed cooperative reinforcement
learning algorithm in which agents in a network communicate only with their immediate …

Consider a set of nodes distributed spatially over some region forming a network, where
every node takes measurements of an underlying process. The objective is for every node in …

A conventional multichannel narrowband active noise control (MNANC) system can
effectively suppress low-frequency periodic noise. However, a large number of secondary …

Distributed processing over networks relies on in-network processing and cooperation
among neighboring agents. Cooperation is beneficial when agents share a common …

In this paper, we consider learning dictionary models over a network of agents, where each
agent is only in charge of a portion of the dictionary elements. This formulation is relevant in …

In this brief, a proportionate robust diffusion recursive least exponential hyperbolic cosine
algorithm is proposed for distributed estimation. To be robust against impulsive noise, an …

Distributed estimation over networks has received much attention in recent years due to its
broad applicability. Many signals in nature present high level of sparsity, which contain only …

This is an introduction to multicast routing, which is the study of methods for routing from one
source to many destinations, or from many sources to many destinations. Multicast is …

A family of adaptive-filtering algorithms that uses a variable step size is proposed. A variable
step size is obtained by minimizing the energy of the noise-free a posteriori error signal …