Characterization of ergodic hidden Markov sources

Authors:
Alexander Schönhuth;Herbert Jaeger
Affiliations:
School of Computing Science, Simon Fraser University, Burnaby, BC, Canada;Jacobs University Bremen, School of Engineering and Science, Bremen, Germany
Venue:
IEEE Transactions on Information Theory
Year:
2009

Citing 7
Cited 0

Topics in matrix analysis

Topics in matrix analysis
Entropy and information theory

Entropy and information theory
Quantum walks on graphs

STOC '01 Proceedings of the thirty-third annual ACM symposium on Theory of computing
Observable Operator Models for Discrete Stochastic Time Series

Neural Computation
On analytic properties of entropy rate

IEEE Transactions on Information Theory
Hidden Markov processes

IEEE Transactions on Information Theory
Asymptotic Mean Stationarity of Sources With Finite Evolution Dimension

IEEE Transactions on Information Theory

Quantified Score

Hi-index	754.84

Visualization

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.