This paper deals with the distributed state estimation problem for a class of sensor networks
described by discrete-time stochastic systems with randomly varying nonlinearities and …

We propose a novel distributed algorithm to cluster graphs. The algorithm recovers the
solution obtained from spectral clustering without the need for expensive eigenvalue …

In this paper, the distributed state estimation problem is investigated for a class of sensor
networks described by uncertain discrete‐time dynamical systems with Markovian jumping …

This article is concerned with the robust distributed state estimation problem for a class of
uncertain sensor networks with multiple stochastic communication delays. A sequence of …

This article is concerned with a new distributed state estimation problem for a class of
dynamical systems in sensor networks. The target plant is described by a set of differential …

We adjust the node and edge weightings of graphs using convex optimization to impose
bounds on their Laplacian spectra. First, we derive necessary and sufficient conditions that …

We present a methodology and a software framework for the automatic design exploration of
the communication network among sensors, actuators and controllers in building automation …

The Markov Chain Distributed Particle Filter (MCDPF) is an algorithm for the nodes in a
sensor network to cooperatively run a particle filter, based on each sensor making updates …

We propose a novel distributed algorithm to compute eigenvectors and eigenvalues of the
graph Laplacian matrix L. We prove that, by propagating waves through the graph, a local …

We adjust the node and edge weightings of graphs using convex optimization to impose
bounds on their Laplacian spectra. We first derive necessary and sufficient conditions that …