Fundamentals of Stochastic Filtering

The objective of stochastic filtering is to determine the best estimate for the state of a stochastic dynamical system from partial observations. The solution of this problem in the linear case is the well known Kalman-Bucy filter which has found widespread practical application. The purpose of this...

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Bibliographic Details
Call Number:Libro Electrónico
Main Authors: Bain, Alan (Author), Crisan, Dan (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:Inglés
Published: New York, NY : Springer New York : Imprint: Springer, 2009.
Edition:1st ed. 2009.
Series:Stochastic Modelling and Applied Probability, 60
Subjects:
Probabilities.
Control engineering.
Robotics.
Automation.
Numerical analysis.
Social sciences-Mathematics.
Probability Theory.
Control, Robotics, Automation.
Numerical Analysis.
Mathematics in Business, Economics and Finance.
Online Access:Texto Completo
Table of Contents:
  • Filtering Theory
  • The Stochastic Process ?
  • The Filtering Equations
  • Uniqueness of the Solution to the Zakai and the Kushner-Stratonovich Equations
  • The Robust Representation Formula
  • Finite-Dimensional Filters
  • The Density of the Conditional Distribution of the Signal
  • Numerical Algorithms
  • Numerical Methods for Solving the Filtering Problem
  • A Continuous Time Particle Filter
  • Particle Filters in Discrete Time.

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