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210512 ||| eng |
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|a 1000083492
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|a 9783731508076
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|a Rhode, Stephan
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|a Robust and Regularized Algorithms for Vehicle Tractive Force Prediction and Mass Estimation
|h Elektronische Ressource
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| 260 |
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|b KIT Scientific Publishing
|c 2018
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| 300 |
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|a 1 electronic resource (XXIV, 196 p. p.)
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| 653 |
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|a Onlinefilter
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| 653 |
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|a recursive estimation
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| 653 |
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|a robust estimation
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| 653 |
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|a Systemidentifikation
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| 653 |
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|a system identification
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| 653 |
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|a Robuste Schätzer
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| 653 |
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|a Technology: general issues / bicssc
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| 653 |
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|a Total Least Squares
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| 653 |
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|a errors-in-variables
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| 041 |
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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 Karlsruher Schriftenreihe Fahrzeugsystemtechnik / Institut für Fahrzeugsystemtechnik
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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 |
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|a 10.5445/KSP/1000083492
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| 856 |
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|u https://directory.doabooks.org/handle/20.500.12854/58556
|z DOAB: description of the publication
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|u https://www.ksp.kit.edu/9783731508076
|7 0
|x Verlag
|3 Volltext
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|a 600
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|a This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models.
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