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- W4372260419 abstract "The problem of quickest change detection in a sequence of independent observations is considered. The pre-change distribution is assumed to be known, while the post-change distribution is completely unknown. A window-limited leave-one-out (LOO) CuSum test is developed, which does not assume any knowledge of the post-change distribution, and does not require any post-change training samples. It is shown that, with certain convergence conditions on the density estimator, the LOO-CuSum test is first-order asymptotically optimal, as the false alarm rate goes to zero. The analysis is validated through numerical results, where the LOO-CuSum test is compared with baseline tests that have distributional knowledge." @default.
- W4372260419 created "2023-05-07" @default.
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- W4372260419 creator A5091099445 @default.
- W4372260419 date "2023-06-04" @default.
- W4372260419 modified "2023-09-27" @default.
- W4372260419 title "Quickest Change Detection with Leave-one-out Density Estimation" @default.
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- W4372260419 doi "https://doi.org/10.1109/icassp49357.2023.10096341" @default.
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