Optimal Detection of Random Walks on Graphs: Performance Analysis via Statistical Physics

Abstract

We study the problem of detecting a random walk on a graph from a sequence of noisy measurements at every node. There are two hypotheses: either every observation is just meaningless zero-mean Gaussian noise, or at each time step exactly one node has an elevated mean, with its location following a random walk on the graph over time. We want to exploit… (More)

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