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Mathematical and Computational Applications is published by MDPI from Volume 21 Issue 1 (2016). Articles in this Issue were published by another publisher in Open Access under a CC-BY (or CC-BY-NC-ND) licence. Articles are hosted by MDPI on mdpi.com as a courtesy and upon agreement with the previous journal publisher.
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Math. Comput. Appl. 2004, 9(3), 457-462; https://doi.org/10.3390/mca9030457

Informativeness of Parallel Kalman Filters

Istanbul Technical University, Faculty of Aeronautics and Astronautics, 34469 Maslak, Turkey
Published: 1 December 2004
PDF [1420 KB, uploaded 1 April 2016]

Abstract

This article considers the informativeness of parallel Kalman filters. Expressions are derived for determination of the amount of information obtained by additional measurements with a reserved measurement channel during processing. The theorems asserting that there is an increase in the informativeness of Kalman filters when there is a failure-free reserved measurement channel are proved.
Keywords: Dynamic system; Information theory; Kalman Filter; Multichannel measurement systems Dynamic system; Information theory; Kalman Filter; Multichannel measurement systems
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).
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Hajiyev, C. Informativeness of Parallel Kalman Filters. Math. Comput. Appl. 2004, 9, 457-462.

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