In this paper, the advances of distributed fusion estimation (DFE) algorithms for multi-sensor
networked systems (NSs) are reviewed. First, several general DFE algorithms are reviewed …

We propose an open-loop and a closed-loop stochastic event-triggered sensor schedule for
remote state estimation. Both schedules overcome the essential difficulties of existing …

We establish minimax risk lower bounds for distributed statistical estimation given a budget
$ B $ of the total number of bits that may be communicated. Such lower bounds in turn …

We study deterministic mean-location parameter estimation when only quantized versions of
the original observations are available, due to bandwidth constraints. When the dynamic …

This paper discusses nonparametric distributed learning. After reviewing the classical
learning model and highlighting the success of machine learning in centralized settings, the …

This paper provides an overview of distributed estimation-compression problems
encountered with wireless sensor networks (WSN). A general formulation of distributed …

We consider the optimal power scheduling problem for the decentralized estimation of a
noise-corrupted deterministic signal in an inhomogeneous sensor network. Sensor …

Distributed estimation based on measurements from multiple wireless sensors is
investigated. It is assumed that a group of sensors observe the same quantity in …

Wireless sensor networks (WSNs) deployed to perform surveillance and monitoring tasks
have to operate under stringent energy and bandwidth limitations. These motivate well …

We derive linear estimators of stationary random signals based on reduced-dimensionality
observations collected at distributed sensors and communicated to a fusion center over …