Change detection with unknown post-change parameter using Kiefer-Wolfowitz method

We consider a change detection problem with an unknown post-change parameter. The optimal algorithm in minimizing worst case detection delay subject to a constraint on average run length, referred as parallel CUSUM, is computationally expensive. We propose a low complexity algorithm based on paramet...

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Bibliographic Details
Published in:	Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 3919 - 3923
Main Authors:	Singamasetty, Vijay, Nair, Navneeth, Bhashyam, Srikrishna, Pachai Kannu, Arun
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.03.2017
Subjects:	average run length Change detection algorithms Convergence CUSUM Delays Detection delay false alarm probability Kiefer-Wolfowitz algorithm Mathematical model Tuning
ISSN:	2379-190X
Online Access:	Get full text
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Summary:	We consider a change detection problem with an unknown post-change parameter. The optimal algorithm in minimizing worst case detection delay subject to a constraint on average run length, referred as parallel CUSUM, is computationally expensive. We propose a low complexity algorithm based on parameter estimation using Kiefer-Wolfowitz (KW) method with CUSUM based change detection. We also consider a variant of KW method where the tuning sequences of KW method are reset periodically. We study the performance under the Gaussian mean change model. Our results show that reset KW-CUSUM performs close to the parallel CUSUM in terms of worst case delay versus average run length. Non-reset KW-CUSUM algorithm has smaller probability of false alarm compared to the existing algorithms, when run over a finite duration.
ISSN:	2379-190X
DOI:	10.1109/ICASSP.2017.7952891