Publication: Informativeness of Parallel Kalman Filters
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MDPI AG
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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.
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Mathematical and Computational Applications
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OPEN
Keywords
Signal theory (characterization, reconstruction, filtering, etc.), Measures of information, entropy, Information theory, Multichannel measurement systems, Kalman filter, Dynamic system, Kalman Filter, Filtering in stochastic control theory, Signal detection and filtering (aspects of stochastic processes)