{"product_id":"nonlinear-state-and-parameter-estimation-of-spatially-distributed-systems-von-felix-sawo","title":"Nonlinear state and parameter estimation of spatially distributed systems","description":"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.\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9783866443709\"\u003e\u003ch3\u003e\u003c\/h3\u003e\u003c\/div\u003e","brand":"Libri","offers":[{"title":"Softcover - 9783866443709","offer_id":39457289470045,"sku":"9783866443709","price":30.9,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/847f7a91-2e39-4a4f-ac76-06b29a558d60.jpg?v=1781586736","url":"https:\/\/shop.autorenwelt.de\/products\/nonlinear-state-and-parameter-estimation-of-spatially-distributed-systems-von-felix-sawo","provider":"Autorenwelt Shop","version":"1.0","type":"link"}