Quickest Detection of Deviations from Periodic Statistical Behavior

Taposh Banerjee; Prudhvi Gurram; Gene T. Whipps

ICASSP 2019accepted0 citations

Quickest Detection of Deviations from Periodic Statistical Behavior

Taposh Banerjee, Prudhvi Gurram, Gene T. Whipps

Abstract

A new class of stochastic processes called independent and periodically identically distributed (i.p.i.d.) processes is defined to capture periodically varying statistical behavior. Algorithms are proposed to detect changes in such i.p.i.d. processes. It is shown that the algorithms can be computed recursively and are asymptotically optimal. This problem has applications in anomaly detection in traffic data, social network data, and neural data, where periodic statistical behavior has been observed.

BibTeX

@inproceedings{icassp2019_quickestdetectio,
  title = {Quickest Detection of Deviations from Periodic Statistical Behavior},
  author = {Taposh Banerjee and Prudhvi Gurram and Gene T. Whipps},
  booktitle = {ICASSP 2019},
  year = {2019}
}