Nonlinear state and parameter estimation of spatially distributed systems - ISBN:3866443706

Nonlinear state and parameter estimation of spatially distributed systems

Date: 24 November 2010, 15:41

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Felix Sawo, "Nonlinear state and parameter estimation of spatially distributed systems"
Publisher: Kit Scientific Publishing | 2009 | ISBN: 3866443706 | PDF | 178 pages | 20.8 MB

Abstract: 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.

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