Nonlinear state and parameter estimation of spatially distributed systems

Sawo, Felix:

ISBN 10: 3866443706 / ISBN 13: 9783866443709

Published by KIT Scientific Publishing, 2009

About this Item

153 S. 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. B05-04-03C Sprache: Englisch Gewicht in Gramm: 300.

Seller Inventory # 1834953

Bibliographic Details

• Title: Nonlinear state and parameter estimation of spatially distributed systems
• Publisher: KIT Scientific Publishing
• Publication Date: 2009
• Language: English
• ISBN 10: 3866443706
• ISBN 13: 9783866443709
• Binding: 8° Paperback
• Condition: Sehr gut
• Weight: 300 grams
• Seller catalogs:
  • Physik

About this title

Synopsis

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.