An unscented transformation approach to stochastic analysis of measurement uncertainty in magnet resonance imaging with applications in engineering
DOI10.34768/amcs-2021-0006zbMath1469.93104OpenAlexW3188847507MaRDI QIDQ2042986
Kristine John, Martin Bruschewski, Andreas Rauh, Carolin Wüstenhagen, Sven Grundmann
Publication date: 22 July 2021
Published in: International Journal of Applied Mathematics and Computer Science (Search for Journal in Brave)
Full work available at URL: https://hal-ensta-bretagne.archives-ouvertes.fr/hal-03193381
Applications of statistics in engineering and industry; control charts (62P30) Filtering in stochastic control theory (93E11) Nonlinear systems in control theory (93C10) Discrete-time control/observation systems (93C55)
Cites Work
- A second-order TV-based coupling model and an ADMM algorithm for MR image reconstruction
- A decomposition approach to type 2 interval arithmetic
- Exploiting multi-core and many-core parallelism for subspace clustering
- Integrodifferential approaches to frequency analysis and control design for compressible fluid flow in a pipeline element
- A new method for the nonlinear transformation of means and covariances in filters and estimators
- Towards Analyzing the Influence of Measurement Errors in Magnetic Resonance Imaging of Fluid Flows
- Matrix Multiplication and Fast Fourier Transforms
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- Unnamed Item
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