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About Nonlinear state and parameter estimation of spatially distributed systems
In this book 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.
Detailed Information
| Author: | Sawo F. |
|---|---|
| Publication Year: | 2009 |
| ISBN: | 9783866443709 |
| Pages: | 178 |
| Language: | English |
| File Size: | 8.647 |
| Format: | |
| Price: | FREE |
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