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Nonlinear state and parameter estimation of spatially distributed systems
- Format:
- Book
- Author/Creator:
- Sawo, Felix
- Series:
- Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe / Intelligent Sensor-Actuator-Systems Laboratory
- Language:
- English
- Physical Description:
- 1 online resource (XI, 153 p. p.)
- Place of Publication:
- KIT Scientific Publishing 2009
- Language Note:
- English
- Summary:
- In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion.
- ISBN:
- 1000011485
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