Cart (Loading....) | Create Account
Close category search window

Adaptive algorithms and Markov chain Monte Carlo methods

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Solo, V. ; Dept. of Stat., Macquarie Univ., North Ryde, NSW, Australia

Many signal processing and control problems are complicated by the presence of unobserved variables and/or auxiliary variables measured with error. In nonlinear settings this causes problems in constructing adaptive parameter estimators. In off-line situations so-called Markov chain Monte Carlo methods have recently become popular for solving these kinds of problems. In this paper we explore the development of online Markov chain Monte Carlo techniques for adaptive parameter estimation

Published in:

Decision and Control, 1999. Proceedings of the 38th IEEE Conference on  (Volume:2 )

Date of Conference:


Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.