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

Modeling temporal dependence of spherically invariant random vectors with triplet markov chains

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

2 Author(s)
Brunel, N. ; CITI Dept., CNRS, Evry ; Pieczynski, W.

Our paper deals with multivariate hidden Markov chains (MHMC) with a view towards segmentation. We propose a new model in which temporal dependencies are modelled using copulas and sensor dependencies are represented by spherically invariant random vector (SIRV). Copulas are very useful and flexible tools, which have been little applied in signal processing problems until now. In particular, for some desirable marginal distributions it is possible to obtain different kind of dependencies. Using some recent results on triplet Markov chains, the new model extends the case of MHMC when the observations are SIRV and independent conditionally on the states. We propose algorithms for computing efficiently the posterior probabilities of the involved triplet Markov chain, in order to propose rapid segmentation and estimation procedures

Published in:

Statistical Signal Processing, 2005 IEEE/SP 13th Workshop on

Date of Conference:

17-20 July 2005

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.