G
Georgios Fellouris
Researcher at University of Illinois at Urbana–Champaign
Publications - 56
Citations - 594
Georgios Fellouris is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Change detection & False alarm. The author has an hindex of 13, co-authored 47 publications receiving 518 citations. Previous affiliations of Georgios Fellouris include Columbia University & University of Southern California.
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Decentralized Sequential Hypothesis Testing Using Asynchronous Communication
TL;DR: It is shown theoretically and corroborate with simulations that the performance of the suggested test in discrete time can be significantly improved when the sensors sample their underlying continuous time processes more frequently, a property which is not enjoyed by other centralized or decentralized tests in the literature.
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Decentralized Sequential Hypothesis Testing using Asynchronous Communication
TL;DR: In this article, the authors present a test for decentralized sequential hypothesis testing, which is asymptotically optimum in the case of continuous time and continuous path signals, while in discrete time this strong optimality property is preserved under proper conditions.
Journal ArticleDOI
Second-Order Asymptotic Optimality in Multisensor Sequential Change Detection
TL;DR: A generalized multisensor sequential change detection problem is considered, in which a number of (possibly correlated) sensors monitor an environment in real time, the joint distribution of their observations is determined by a global parameter vector, and at some unknown time there is a change in an unknown subset of components of this parameter vector.
Proceedings ArticleDOI
Sequential anomaly detection with observation control
TL;DR: The problem of anomaly detection is considered when multiple processes are observed sequentially, but it is possible to sample only a subset of them at a time according to an adaptive sampling policy, and the optimal asymptotic performance as the error probabilities vanish is obtained.
Journal ArticleDOI
Quickest Change Detection Under Transient Dynamics: Theory and Asymptotic Analysis
TL;DR: In this paper, the authors considered the problem of quickest change detection under transient dynamics, where the change from the initial distribution to the final persistent distribution does not happen instantaneously, but after a series of transient phases.