Minimum Redundancy Coding for Uncertain Sources

Details Minimum Redundancy Coding for Uncertain Sources Minimum Redundancy Coding for Uncertain Sources

2011-02-14

arxiv.org/abs/1102.2678v2

Computer Science

Information Theory

5 pages

Scientific paper

Consider the set of source distributions within a fixed maximum relative entropy with respect to a given nominal distribution. Lossless source coding over this relative entropy ball can be approached in more than one way. A problem previously considered is finding a minimax average length source code. The minimizing players are the codeword lengths --- real numbers for arithmetic codes, integers for prefix codes --- while the maximizing players are the uncertain source distributions. Another traditional minimizing objective is the first one considered here, maximum (average) redundancy. This problem reduces to an extension of an exponential Huffman objective treated in the literature but heretofore without direct practical application. In addition to these, this paper examines the related problem of maximal minimax pointwise redundancy and the problem considered by Gawrychowski and Gagie, which, for a sufficiently small relative entropy ball, is equivalent to minimax redundancy. One can consider both Shannon-like coding based on optimal real number ("ideal") codeword lengths and a Huffman-like optimal prefix coding.

Affiliated with

Also associated with

No associations

Rating

Minimum Redundancy Coding for Uncertain Sources does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Minimum Redundancy Coding for Uncertain Sources, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Minimum Redundancy Coding for Uncertain Sources will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-215098