Bayesian Filtering and Smoothing

Bayesian Filtering and Smoothing
Author :
Publisher : Cambridge University Press
Total Pages : 255
Release :
ISBN-13 : 9781107030657
ISBN-10 : 110703065X
Rating : 4/5 (5X Downloads)

Book Synopsis Bayesian Filtering and Smoothing by : Simo Särkkä

Download or read book Bayesian Filtering and Smoothing written by Simo Särkkä and published by Cambridge University Press. This book was released on 2013-09-05 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.


Bayesian Filtering and Smoothing Related Books

Bayesian Filtering and Smoothing
Language: en
Pages: 255
Authors: Simo Särkkä
Categories: Computers
Type: BOOK - Published: 2013-09-05 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.
Bayesian Filtering and Smoothing
Language: en
Pages: 0
Authors: Simo Särkkä
Categories: Mathematics
Type: BOOK - Published: 2013-09-05 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

Filtering and smoothing methods are used to produce an accurate estimate of the state of a time-varying system based on multiple observational inputs (data). In
Bayesian Bounds for Parameter Estimation and Nonlinear Filtering/Tracking
Language: en
Pages: 951
Authors: Harry L. Van Trees
Categories: Technology & Engineering
Type: BOOK - Published: 2007-08-31 - Publisher: Wiley-IEEE Press

DOWNLOAD EBOOK

The first comprehensive development of Bayesian Bounds for parameter estimation and nonlinear filtering/tracking Bayesian estimation plays a central role in man
Bayesian Inference of State Space Models
Language: en
Pages: 503
Authors: Kostas Triantafyllopoulos
Categories: Mathematics
Type: BOOK - Published: 2021-11-12 - Publisher: Springer Nature

DOWNLOAD EBOOK

Bayesian Inference of State Space Models: Kalman Filtering and Beyond offers a comprehensive introduction to Bayesian estimation and forecasting for state space
Sequential Monte Carlo Methods in Practice
Language: en
Pages: 590
Authors: Arnaud Doucet
Categories: Mathematics
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Monte Carlo methods are revolutionizing the on-line analysis of data in many fileds. They have made it possible to solve numerically many complex, non-standard