Characterization of Ergodic Hidden Markov Sources

Author

Schönhuth, Alexander ; Jaeger, Herbert

Author_Institution

Sch. of Comput. Sci., Simon Fraser Univ., Burnaby, BC

Volume

Issue

fYear

2009

fDate

5/1/2009 12:00:00 AM

Firstpage

2107

Lastpage

2118

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;

fLanguage

English

Journal_Title

Information Theory, IEEE Transactions on

Publisher

ieee

ISSN

0018-9448

Type

jour

DOI

10.1109/TIT.2009.2016041

Filename

4839026

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=749920