caa a22 4500 477097065 CHVBK 20180405111530.0 cr unu---uuuuu 170330e19960501xx s 000 0 eng 10.1007/BF01182588 doi (NATIONALLICENCE)springer-10.1007/BF01182588 Chowdhury Fahmida Department of Electrical Engineering, Michigan Technological University, 49931, Houghton, Michigan aut Kalman filter with hypothesis testing: A tool for estimating uncertain parameters [Elektronische Daten] [Fahmida Chowdhury] In this paper we present a simple and practical algorithm for the estimation of uncertain parameters of linear systems. The uncertainty is twofold, involving random observation noise, and possible jumps in the parameter values. The jumps may occur at unknown points in time, and are of unknown magnitudes and directions. The algorithm is based on the Kalman filter, with a single-sample hypothesis test, which is used to employ a three-state decision rule (yes, no, maybe). The "maybe” choice invokes a fading memory Kalman filter. The overall algorithm contains the constant parameter filter, fading memory filter, and the set of tests and rules that enable it to switch back and forth between the two filters. Application examples are presented. Birkhäuser Boston, 1996 Circuits, Systems and Signal Processing Birkhäuser-Verlag 15/3(1996-05-01), 291-311 0278-081X 15:3<291 1996 15 34 https://doi.org/10.1007/BF01182588 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF01182588 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Chowdhury Fahmida Department of Electrical Engineering, Michigan Technological University, 49931, Houghton, Michigan aut NATIONALLICENCE 773 0- Circuits, Systems and Signal Processing Birkhäuser-Verlag 15/3(1996-05-01), 291-311 0278-081X 15:3<291 1996 15 34 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer