By Topic

Identification via compressed data

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)
Ahlswede, R. ; Fakultat fur Math., Bielefeld Univ., Germany ; En-hui Yang ; Zhen Zhang

A new coding problem is introduced for a correlated source (Xn,Yn)n=1. The observer of Xn can transmit data depending on Xn at a prescribed rate R. Based on these data the observer of Yn tries to identify whether for some distortion measure ρ (like the Hamming distance) n-1 ρ(Xn,Y n)⩽d, a prescribed fidelity criterion. We investigate as functions of R and d the exponents of two error probabilities, the probabilities for misacceptance, and the probabilities for misrejection. In the case where Xn and Yn are independent, we completely characterize the achievable region for the rate R and the exponents of two error probabilities; in the case where Xn and Yn are correlated, we get some interesting partial results for the achievable region. During the process, we develop a new method for proving converses, which is called “the inherently typical subset lemma”. This new method goes considerably beyond the “entropy characterization” the “image size characterization,” and its extensions. It is conceivable that this new method has a strong impact on multiuser information theory

Published in:

Information Theory, IEEE Transactions on  (Volume:43 ,  Issue: 1 )