Quickest Change Detection with Confusing Change
<|reference_start|>Quickest Change Detection with Confusing Change: In the problem of quickest change detection (QCD), a change occurs at some unknown time in the distribution of a sequence of independent observations. This work studies a QCD problem where the change is either a bad change, which we aim to detect, or a confusing change, which is not of our interest. Our objective is to detect a bad change as quickly as possible while avoiding raising a false alarm for pre-change or a confusing change. We identify a specific set of pre-change, bad change, and confusing change distributions that pose challenges beyond the capabilities of standard Cumulative Sum (CuSum) procedures. Proposing novel CuSum-based detection procedures, S-CuSum and J-CuSum, leveraging two CuSum statistics, we offer solutions applicable across all kinds of pre-change, bad change, and confusing change distributions. For both S-CuSum and J-CuSum, we provide analytical performance guarantees and validate them by numerical results. Furthermore, both procedures are computationally efficient as they only require simple recursive updates.<|reference_end|>
@article{chen2024quickest,
    title={Quickest Change Detection with Confusing Change},
    author={Yu-Zhen Janice Chen, Jinhang Zuo, Venugopal V. Veeravalli, Don Towsley},
    journal={arXiv preprint arXiv:2405.00842},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.00842},
    primaryClass={math.ST cs.IT cs.LG eess.SP math.IT math.OC stat.TH}
}