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

How to Tell a Bad Filter Through Monte Carlo Simulations

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

3 Author(s)
Lingji Chen ; Sci. Syst. Co. Inc., Woburn ; Chihoon Lee ; Mehra, R.K.

In this note, we propose one particular method to address the issue of how to numerically evaluate nonlinear filtering algorithms and/or their software implementations, through Monte Carlo simulations. We introduce a quantitative performance indicator whose computation can be automated and does not depend on any specific definition of point estimate. The method is based on conditional probability integral transform and maximum deviation of an empirical cumulative distribution function from a uniform distribution. The usefulness of such an indicator is illustrated through an example.

Published in:

Automatic Control, IEEE Transactions on  (Volume:52 ,  Issue: 7 )

Date of Publication:

July 2007

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.