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Analysis of a low-complexity change detection scheme
KTH, Superseded Departments, Signals, Sensors and Systems.ORCID iD: 0000-0002-1927-1690
2000 (English)In: International journal of adaptive control and signal processing (Print), ISSN 0890-6327, E-ISSN 1099-1115, Vol. 14, no 5, 481-503 p.Article in journal (Refereed) Published
Abstract [en]

In many applications, for example in fault detection, it is important to discriminate between changes in system dynamics and abrupt changes in the disturbance level. A new low-complexity change detection method based on the average behaviour of the estimated impulse response parameters of the normalized least mean-square (NLMS) algorithm is presented. The solution includes second-order Kalman filters based on exponential transient models for parameter convergence. Explicit formulas for time-varying state covariances and Kalman gains are given. The receiver operating characteristics (ROC) is also computed and used for performance evaluation. The effects of the approximations in the averaging analysis that occur for high adaptation gains are handled with an experimental ROC analysis.

Place, publisher, year, edition, pages
2000. Vol. 14, no 5, 481-503 p.
Keyword [en]
Adaptive algorithms, Approximation theory, Kalman filtering, Mathematical models, Matrix algebra, Parameter estimation, Riccati equations, Signal receivers, Time varying systems, Low complexity change detection, Normalized least mean square, Receiver operating characteristics, Transient models, Signal detection
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-55410DOI: 10.1002/1099-1115(200008)14:5<481::AID-ACS602>3.0.CO;2-POAI: diva2:471623

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Available from: 2012-01-02 Created: 2012-01-02 Last updated: 2016-05-27Bibliographically approved

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