Entropic measures, Markov information sources and complexity
This paper, which could be thought of as a review paper, discusses Shannon's entropy and entropy rate for discrete and continuous Markov sources, with finite and continuous alphabets. After a prerequisite on some known results, it examines the relations between program-size complexity, algorithmic probability and entropy of Markov information sources with a binary alphabet and discrete time.
scientific article; zbMATH DE number 1861218
scientific article