By Topic

Minimax Pointwise Redundancy for Memoryless Models Over Large Alphabets

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)
Szpankowski, W. ; Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA ; Weinberger, M.J.

We study the minimax pointwise redundancy of universal coding for memoryless models over large alphabets and present two main results. We first complete studies initiated in Orlitsky and Santhanam deriving precise asymptotics of the minimax pointwise redundancy for all ranges of the alphabet size relative to the sequence length. Second, we consider the minimax pointwise redundancy for a family of models in which some symbol probabilities are fixed. The latter problem leads to a binomial sum for functions with superpolynomial growth. Our findings can be used to approximate numerically the minimax pointwise redundancy for various ranges of the sequence length and the alphabet size. These results are obtained by analytic techniques such as tree-like generating functions and the saddle point method.

Published in:

Information Theory, IEEE Transactions on  (Volume:58 ,  Issue: 7 )