Stochastic Modelling and Filtering

Proceedings of the IFIP-WG 7/1 Working Conference, Rome, Italy, December 10¿14, 1984
Herausgegeben:Germani, Alfredo

• Broschiertes Buch

Produktbeschreibung

Optimization of drugs' action.- Nonlinear stochastic evolution equations in Hilbert spaces.- Equivalence and reversibility of point processes.- Galerkin approximation for optimal linear filtering of infinite dimensional linear systems.- On conditionally linear filtering, control, and coding.- Martingale problems for controlled processes.- Estimation of immune response model parameters based on maximum likelihood method.- Approximate impulse control of partially observed systems.- The averaging principle for a class of stochastic algorithms in adaptive filtering.- Asymptotic study of estimation problems with small observation noise.- Filtering on manifolds.- Finite-dimensionality in discrete-time nonlinear filtering from a bayesian statistics viewpoint.- On the innovations problem for a finite additive white noise approach to nonlinear filtering.- Classification of discretization schemes of diffusions according to an ergodic criterium.

Produktdetails

• Lecture Notes in Control and Information Sciences 91
• Verlag: Springer / Springer Berlin Heidelberg / Springer, Berlin
• Artikelnr. des Verlages: 978-3-540-17575-9
• 1987.
• Seitenzahl: 228
• Erscheinungstermin: 31. März 1987
• Englisch
• Abmessung: 244mm x 170mm x 13mm
• Gewicht: 401g
• ISBN-13: 9783540175759
• ISBN-10: 354017575X
• Artikelnr.: 39602799

Inhaltsangabe

Optimization of drugs' action.- Nonlinear stochastic evolution equations in Hilbert spaces.- Equivalence and reversibility of point processes.- Galerkin approximation for optimal linear filtering of infinite dimensional linear systems.- On conditionally linear filtering, control, and coding.- Martingale problems for controlled processes.- Estimation of immune response model parameters based on maximum likelihood method.- Approximate impulse control of partially observed systems.- The averaging principle for a class of stochastic algorithms in adaptive filtering.- Asymptotic study of estimation problems with small observation noise.- Filtering on manifolds.- Finite-dimensionality in discrete-time nonlinear filtering from a bayesian statistics viewpoint.- On the innovations problem for a finite additive white noise approach to nonlinear filtering.- Classification of discretization schemes of diffusions according to an ergodic criterium.