TY - GEN
T1 - Quickest Change Detection with Leave-one-out Density Estimation
AU - Liang, Yuchen
AU - Veeravalli, Venugopal V.
N1 - This work was supported in part by the National Science Foundation under grant ECCS-2033900, and by the Army Research Laboratory under Co-operative Agreement W911NF-17-2-0196, through the University of Illinois at Urbana-Champaign.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - (kernel) density estimation
KW - non-parametric statistics
KW - Quickest change detection (QCD)
UR - http://www.scopus.com/inward/record.url?scp=86000385426&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP49357.2023.10096341
DO - 10.1109/ICASSP49357.2023.10096341
M3 - Conference contribution
AN - SCOPUS:86000385426
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
BT - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 48th IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2023
Y2 - 4 June 2023 through 10 June 2023
ER -