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

Minimax discrimination for observed Poisson processes with uncertain rate functions

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)

The problem of robust design is considered in the context of testing hypotheses concerning the rate function of an observed point process. Designs that are insensitive to uncertainty in the rate functions are developed by applying a minimax formulation to two different measures of signal-to-noise ratio. Uncertainty in the rate is modeled by using general classes of rate measures generated by Choquet 2-alternating capacities, and solutions are characterized for this case by a Radon-Nikodym type derivative between such classes. It is shown that for uncertainty within capacity classes the robust decision design developed for the signal-to-noise ratio is also robust in a weaker sense for the Chernoff upper bounds on the error probabilities. Furthermore, the use of such a test guarantees the exponential convergence of these bounds to zero with increasing length of the observation interval for all rates in the uncertainty class.

Published in:

Information Theory, IEEE Transactions on  (Volume:31 ,  Issue: 5 )

Date of Publication:

Sep 1985

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.