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ORCIDVesa Klumpp
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2020 – today
- 2023
[c20]Jana Mayer, Vesa Klumpp, Jonas Hillenbrand, Benjamin Noack:
Statistical Approach for Preload Monitoring of Ball Screw Drives. SENSORS 2023: 1-4- 2021
- [c19]Michael Grethler, Marin B. Marinov
, Vesa Klumpp:
Embedded Machine Learning for Machine Condition Monitoring. FABULOUS 2021: 217-228
2010 – 2019
- 2010
- [c18]Henning P. Eberhardt, Vesa Klumpp, Uwe D. Hanebeck:
Optimal dirac approximation by exploiting independencies. ACC 2010: 1392-1398 - [c17]Marcus Baum, Vesa Klumpp, Uwe D. Hanebeck:
A novel Bayesian method for fitting a circle to noisy points. FUSION 2010: 1-6 - [c16]Henning P. Eberhardt, Vesa Klumpp, Uwe D. Hanebeck:
Density trees for efficient nonlinear state estimation. FUSION 2010: 1-8 - [c15]Vesa Klumpp, Frederik Beutler, Uwe D. Hanebeck, Dietrich Fränken:
The Sliced Gaussian Mixture Filter with adaptive state decomposition depending on linearization error. FUSION 2010: 1-8 - [c14]Vesa Klumpp, Benjamin Noack, Marcus Baum, Uwe D. Hanebeck:
Combined set-theoretic and stochastic estimation: A comparison of the SSI and the CS filter. FUSION 2010: 1-8 - [c13]Benjamin Noack, Vesa Klumpp, Nikolay Petkov, Uwe D. Hanebeck:
Bounding linearization errors with sets of densities in approximate Kalman filtering. FUSION 2010: 1-8
2000 – 2009
- 2009
- [c12]Uwe D. Hanebeck, Marco F. Huber, Vesa Klumpp:
Dirac mixture approximation of multivariate Gaussian densities. CDC 2009: 3851-3858 - [c11]Julian Hörst, Felix Sawo, Vesa Klumpp, Uwe D. Hanebeck, Dietrich Fränken:
Extension of the Sliced Gaussian Mixture Filter with application to cooperative passive target tracking. FUSION 2009: 587-594 - [c10]Benjamin Noack, Vesa Klumpp, Uwe D. Hanebeck:
State estimation with sets of densities considering stochastic and systematic errors. FUSION 2009: 1751-1758 - [c9]Vesa Klumpp, Uwe D. Hanebeck:
Bayesian estimation with uncertain parameters of probability density functions. FUSION 2009: 1759-1766 - [c8]Vesa Klumpp, Uwe D. Hanebeck:
Nonlinear fusion of multi-dimensional densities in joint state space. FUSION 2009: 2044-2051 - 2008
- [c7]Vesa Klumpp, Felix Sawo, Uwe D. Hanebeck, Dietrich Fränken:
The sliced Gaussian mixture filter for efficient nonlinear estimation. FUSION 2008: 1-8 - [c6]Benjamin Noack, Vesa Klumpp, Dietrich Brunn, Uwe D. Hanebeck:
Nonlinear Bayesian estimation with convex sets of probability densities. FUSION 2008: 1-8 - [c5]Felix Sawo, Vesa Klumpp, Uwe D. Hanebeck:
Simultaneous state and parameter estimation of distributed-parameter physical systems based on sliced Gaussian mixture filter. FUSION 2008: 1-8 - [c4]Uwe D. Hanebeck, Vesa Klumpp:
Localized Cumulative Distributions and a multivariate generalization of the Cramér-von Mises distance. MFI 2008: 33-39 - [c3]Vesa Klumpp, Uwe D. Hanebeck:
Direct fusion of Dirac mixture densities using an efficient approximation in joint state space. MFI 2008: 168-174 - [c2]Vesa Klumpp, Uwe D. Hanebeck:
Dirac mixture trees for fast suboptimal multi-dimensional density approximation. MFI 2008: 593-600 - 2006
- [c1]Vesa Klumpp, Dietrich Brunn, Uwe D. Hanebeck:
Approximate Nonlinear Bayesian Estimation Based on Lower and Upper Densities. FUSION 2006: 1-8
Coauthor Index
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