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Quickest Detection in Gauss-Markov Fields by Javad Heydari is a document available to read on EtoBox.

What is Quickest Detection in Gauss-Markov Fields about?

1) The document proposes sequential and data-adaptive detection strategies to detect clusters in Gauss-Markov random fields. This approach aims to improve detection quality and efficiency for large networks where data adaptivity provides gains. 2) The problem is modeled as binary hypothesis testing, where the data is independent under the null hypothesis and dependent (forming a Gauss-Markov random field) under the alternative. 3) Decision rules are derived for general random fields and specialized for G

Author
Javad Heydari
Language
EN