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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Klumpp, V. Noack, B. Baum, M. Hanebeck, U.D. |
| Copyright Year | 2010 |
| Description | Author affiliation: Intell. Sensor-Actuator-Syst. Lab. (ISAS), Karlsruhe Inst. of Technol. (KIT), Karlsruhe, Germany (Klumpp, V.; Noack, B.; Baum, M.; Hanebeck, U.D.) |
| Abstract | In estimation theory, mainly set-theoretic or stochastic uncertainty is considered. In some cases, especially when some statistics of a distribution are not known or additional stochastic information is used in a set-theoretic estimator, both types of uncertainty have to be considered. In this paper, two estimators that cope with combined stochastic and set-theoretic uncertainty are compared, namely the Set-theoretic and Statistical Information filter, which represents the uncertainty by means of random sets, and the Credal State filter, in which the state information is given by sets of probability density functions. The different uncertainty assessment in both estimators leads to different estimation results, even when the prior information and the measurement and system models are equal. This paper explains these differences and states directions, when which estimator should be applied to a given estimation problem. |
| Sponsorship | ISIF |
| Starting Page | 1 |
| Ending Page | 8 |
| File Size | 1402029 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9780982443811 |
| DOI | 10.1109/ICIF.2010.5711908 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-26 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Uncertainty Stochastic processes Random variables Mathematical model Noise Estimation Measurement uncertainty sets of probability densities Filtering state estimation random sets |
| Content Type | Text |
| Resource Type | Article |
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