Title :
Characterization of Ergodic Hidden Markov Sources
Author :
Schönhuth, Alexander ; Jaeger, Herbert
Author_Institution :
Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC
fDate :
5/1/2009 12:00:00 AM
Abstract :
An algebraic criterion for the ergodicity of discrete random sources is presented. For finite-dimensional sources, which contain hidden Markov sources as a subclass, the criterion can be effectively computed. This result is obtained on the background of a novel, elementary theory of discrete random sources, which is based on linear spaces spanned by word functions, and linear operators on these spaces. An outline of basic elements of this theory is provided.
Keywords :
hidden Markov models; statistical mechanics; Markov chain; algebraic criterion; discrete random sources; ergodic hidden Markov sources; finite-dimensional sources; linear spaces; Algorithms; Entropy; Helium; Hidden Markov models; Information theory; Inspection; Polynomials; Probability; Runtime; Testing; Asymptotic mean stationarity; Markov chain; dimension; entropy; ergodic; evolution operator; hidden Markov model; linearly dependent process; observable operator model; random source; stable; state generating function; stationary;
Journal_Title :
Information Theory, IEEE Transactions on
DOI :
10.1109/TIT.2009.2016041
