Data-efficient minimax quickest change detection

• Published in: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 3937 - 3940
• Main Authors: Banerjee, T., Veeravalli, V. V.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.03.2012
• Subjects: Algorithm design and analysis; Approximation algorithms; Bayesian methods; Change detection algorithms; Change point detection; CUSUM; Delay; energy-efficient sensing; observation control; Random variables
• ISBN: 1467300454; 9781467300452
• ISSN: 1520-6149
• DOI: 10.1109/ICASSP.2012.6288779

In [1], a Bayesian two-threshold algorithm was obtained for quickest detection of a change in the distribution of a sequence of random variables, subject to constraints of probability of false alarm and observation cost. This algorithm was shown to be asymptotically optimal and to have good trade-off curves. In this paper, the results in [1] are extended to the more practically relevant minimax setting. Motivated by the structure of the algorithm developed in [1], a CUSUM based algorithm, called DE-CUSUM is proposed, which can be used for on-off observation control and to detect change as quickly as possible subject to a false alarm constraint. It is shown that the DE-CUSUM algorithm inherits the good qualities of the algorithm in [1], i.e., it is also asymptotically optimal and has good trade-off curves. Numerical results show that the DE-CUSUM algorithm provides a substantial savings in the observation cost over the naive approach of fractional sampling.