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210512 ||| eng |
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|a 9783731501244
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|a 1000036878
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1 |
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|a Noack, Benjamin
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| 245 |
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|a State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
|h Elektronische Ressource
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| 260 |
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|b KIT Scientific Publishing
|c 2014
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| 300 |
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|a 1 electronic resource (XVIII, 257 p. p.)
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| 653 |
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|a set-membership estimation
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| 653 |
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|a distributed estimation
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| 653 |
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|a Kalman filter
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| 653 |
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|a Bayesian state estimation
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b DOAB
|a Directory of Open Access Books
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| 490 |
0 |
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|a Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory
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| 500 |
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|a Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/
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| 024 |
8 |
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|a 10.5445/KSP/1000036878
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| 856 |
4 |
2 |
|u https://directory.doabooks.org/handle/20.500.12854/59976
|z DOAB: description of the publication
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| 856 |
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|u https://www.ksp.kit.edu/9783731501244
|7 0
|x Verlag
|3 Volltext
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| 520 |
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|a State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented.
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