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    Autocorrelation-based quickest change detection
    (Institute of Electrical and Electronics Engineers Inc., 2020) Afser, Huseyin; Yabaci, Seyhun Barbaros
    We consider the utilization of the autocorrelation information for aiding the quickest detection problem. Specifically, we investigate the problem of quickly detecting a Gaussian source with autocorrelation such that some of its symbols are repeated as cyclic prefixes. Based on the cumulative sum algorithm, we propose a method which takes advantage of this autocorrelation in order to provide performance improvement compared to the classical energy based detection of the uncorrelated source. © 1997-2012 IEEE.