By Topic

On universal simulation of information sources using training 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

2 Author(s)
Merhav, N. ; Dept. of Electr. Eng., Technion-Israel Inst. of Technol., Haifa, Israel ; Weinberger, M.J.

We consider a universal version of the problem of simulation, where the unknown source to be simulated is represented by a finite training sequence. While in the ordinary simulation problem, the number of random bits per symbol must exceed the entropy H of the source in order to simulate it faithfully, in universal simulation, where the probability law of the target source is always perfectly preserved, H random bits per symbol are still needed to essentially eliminate the statistical dependency between the training sequence and the output sequence.

Published in:

Information Theory, 2002. Proceedings. 2002 IEEE International Symposium on

Date of Conference:

2002