most citedStructurally Observable Distributed Networks of Agents under Cost and Robustness Constraints

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP2018

Spectral Statistics of Directed Networks with Random Link Model Transpose-Asymmetry

Stephen Kruzick, José M. F. Moura

Stochastic network influences complicate graph filter design by producing uncertainty in network iteration matrix eigenvalues, the points at which the graph filter response is defi…

eess.SP2018

Optimal Filter Design for Consensus on Random Directed Graphs

Stephen Kruzick, José M. F. Moura

Optimal design of consensus acceleration graph filters relates closely to the eigenvalues of the consensus iteration matrix. This task is complicated by random networks with uncert…

eess.SP2018

Graph Signal Processing: Filter Design and Spectral Statistics

Stephen Kruzick, José M. F. Moura

Graph signal processing analyzes signals supported on the nodes of a graph by defining the shift operator in terms of a matrix, such as the graph adjacency matrix or Laplacian matr…

eess.SP2017

Consensus State Gram Matrix Estimation for Stochastic Switching Networks from Spectral Distribution Moments

Stephen Kruzick, José M. F. Moura

Reaching distributed average consensus quickly and accurately over a network through iterative dynamics represents an important task in numerous distributed applications. Suitably…

cs.MA20171 cited

Structurally Observable Distributed Networks of Agents under Cost and Robustness Constraints

Stephen Kruzick, Sérgio Pequito, Soummya Kar +2

In many problems, agents cooperate locally so that a leader or fusion center can infer the state of every agent from probing the state of only a small number of agents. Versions of…