By Topic

Asymptotic error probability of binary hypothesis testing for Poisson point-process observations (Corresp.)

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)

It is shown that the asymptotic probability of error of a binary equiprobable hypothesis test for observed Poisson point processes with rates \lambda _{i}(t)=b_{i}(t)+(\rho_{i}(t)+z)^{2}, i=0,1, z \rightarrow \infty , is equal to the error probability of optimum deterministic-signal detection in additive white Gaussian noise when the signals coincide with the square roots of the point-process rates. The implication of this result in the error rate analysis of optical digital communication systems is discussed.

Published in:

Information Theory, IEEE Transactions on  (Volume:32 ,  Issue: 1 )