11 citations · 11 across the 3 of their papers we have counts for
5 papers
Controllability of Coarsely Measured Networked Linear Dynamical Systems (Extended Version)
Nafiseh Ghoroghchian, Rajasekhar Anguluri, Gautam Dasarathy +1
We consider the controllability of large-scale linear networked dynamical systems when complete knowledge of network structure is unavailable and knowledge is limited to coarse sum…
Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
Nafiseh Ghoroghchian, Gautam Dasarathy, Stark C. Draper
We study the problem of community recovery from coarse measurements of a graph. In contrast to the problem of community recovery of a fully observed graph, one often encounters sit…
Node-Centric Graph Learning from Data for Brain State Identification
Nafiseh Ghoroghchian, David M. Groppe, Roman Genov +2
Data-driven graph learning models a network by determining the strength of connections between its nodes. The data refers to a graph signal which associates a value with each graph…
A Hierarchical Graph Signal Processing Approach to Inference from Spatiotemporal Signals
Nafiseh Ghoroghchian, Stark C. Draper, Roman Genov
Motivated by the emerging area of graph signal processing (GSP), we introduce a novel method to draw inference from spatiotemporal signals. Data acquisition in different locations…
Cooperative Abnormality Detection via Diffusive Molecular Communications
Reza Mosayebi, Vahid Jamali, Nafiseh Ghoroghchian +3
In this paper, we consider abnormality detection via diffusive molecular communications (MCs) for a network consisting of several sensors and a fusion center (FC). If a sensor dete…