Main Nonlinear state and parameter estimation of spatially distributed systems
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Nonlinear state and parameter estimation of spatially distributed systems

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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.
Request Code : ZLIBIO831972
Categories:
Year:
2009
Publisher:
Kit Scientific Publishing
Language:
English
Pages:
178
ISBN 10:
3866443706
ISBN 13:
9783866443709
ISBN:
3866443706,9783866443709

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