Computer Science – Information Theory
Scientific paper
2008-05-01
Computer Science
Information Theory
5 pages, to appear in the Proceedings of the 2008 IEEE International Symposium on Information Theory, Toronto, ON, Canada, Jul
Scientific paper
We study the properties of Tsallis entropy and Shannon entropy from the point of view of algorithmic randomness. In algorithmic information theory, there are two equivalent ways to define the program-size complexity K(s) of a given finite binary string s. In the standard way, K(s) is defined as the length of the shortest input string for the universal self-delimiting Turing machine to output s. In the other way, the so-called universal probability m is introduced first, and then K(s) is defined as -log_2 m(s) without reference to the concept of program-size. In this paper, we investigate the properties of the Shannon entropy, the power sum, and the Tsallis entropy of a universal probability by means of the notion of program-size complexity. We determine the convergence or divergence of each of these three quantities, and evaluate its degree of randomness if it converges.
No associations
LandOfFree
The Tsallis entropy and the Shannon entropy of a universal probability 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 The Tsallis entropy and the Shannon entropy of a universal probability, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and The Tsallis entropy and the Shannon entropy of a universal probability will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-340698