Linear time average consensus on fixed graphs and implications for decentralized optimization and multi-agent control
A Olshevsky - arXiv preprint arXiv:1411.4186, 2014 - arxiv.org
We describe a protocol for the average consensus problem on any fixed undirected graph
whose convergence time scales linearly in the total number nodes $ n $. The protocol is …
whose convergence time scales linearly in the total number nodes $ n $. The protocol is …
A unified Bayesian framework for joint estimation and anomaly detection in environmental sensor networks
Advanced large-scale environmental monitoring systems relying on the emerging
aerial/terrestrial technologies of wireless sensor networks (WSNs), unmanned aerial …
aerial/terrestrial technologies of wireless sensor networks (WSNs), unmanned aerial …
Linear time average consensus on fixed graphs
A Olshevsky - IFAC-PapersOnLine, 2015 - Elsevier
We describe a protocol for the average consensus problem on any fixed undirected graph
whose convergence time scales linearly in the total number nodes n. More precisely we …
whose convergence time scales linearly in the total number nodes n. More precisely we …
A novel mobile agent-based distributed evidential expectation maximization algorithm for uncertain sensor networks
M Mozaffari, B Safarinejadian… - Transactions of the …, 2021 - journals.sagepub.com
In this paper, a novel mobile agent-based distributed evidential expectation maximization
(MADEEM) algorithm is presented for sensor networks. The proposed algorithm is used for …
(MADEEM) algorithm is presented for sensor networks. The proposed algorithm is used for …
Distributed faulty node detection in delay tolerant networks: Design and analysis
Propagation of faulty data is a critical issue. In case of Delay Tolerant Networks (DTN) in
particular, the rare meeting events require that nodes are efficient in propagating only …
particular, the rare meeting events require that nodes are efficient in propagating only …
Graph Signal Reconstruction under Heterogeneous Noise via Adaptive Uncertainty-Aware Sampling and Soft Classification
A Fascista, A Coluccia… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Reconstructing bandlimited graph signals from a subset of noisy measurements is a
fundamental challenge within the realm of signal processing. Historically, this problem has …
fundamental challenge within the realm of signal processing. Historically, this problem has …
Randomized algorithms for distributed nonlinear optimization under sparsity constraints
Distributed optimization in multi-agent systems under sparsity constraints has recently
received a lot of attention. In this paper, we consider the in-network minimization of a …
received a lot of attention. In this paper, we consider the in-network minimization of a …
Randomization and quantization for average consensus
B Charron-Bost… - 2018 IEEE Conference on …, 2018 - ieeexplore.ieee.org
Many problems in distributed control reduce to the distributed computation of the average of
initial values in a networked system of autonomous agents, known as the average …
initial values in a networked system of autonomous agents, known as the average …
Distributed estimation from relative measurements of heterogeneous and uncertain quality
This paper studies the problem of estimation from relative measurements in a graph, in
which a vector indexed over the nodes has to be reconstructed from pairwise measurements …
which a vector indexed over the nodes has to be reconstructed from pairwise measurements …
Bias estimation in sensor networks
M Shi, C De Persis, P Tesi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
This article investigates the problem of estimating biases affecting relative state
measurements in a sensor network. Each sensor measures the relative states of its …
measurements in a sensor network. Each sensor measures the relative states of its …