File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Rényi Entropy Rate of Stationary Ergodic Processes

TitleRényi Entropy Rate of Stationary Ergodic Processes
Authors
Keywordscutting
ergodic processes
hidden Markov models
Rényi entropy rate
stacking method
Issue Date1-Jan-2024
PublisherInstitute of Electrical and Electronics Engineers
Citation
IEEE Transactions on Information Theory, 2024, v. 70, n. 1, p. 1-15 How to Cite?
Abstract— In this paper, we examine the Rényi entropy rate of stationary ergodic processes. For a special class of stationary ergodic processes, we prove that the Rényi entropy rate always exists and can be approximated by its defining sequence at most polynomially; moreover, using the Markov approximation method, we show that the Rényi entropy rate can be exponentially approximated by that of the Markov approximating sequence, as the Markov order goes to infinity. For the general case, by constructing a counterexample, we disprove the conjecture that the Rényi entropy rate of a general stationary ergodic process always converges to its Shannon entropy rate as α goes to 1.
Persistent Identifierhttp://hdl.handle.net/10722/347734
ISSN
2023 Impact Factor: 2.2
2023 SCImago Journal Rankings: 1.607

 

DC FieldValueLanguage
dc.contributor.authorWu, Chengyu-
dc.contributor.authorLi, Yonglong-
dc.contributor.authorXu, Li-
dc.contributor.authorHan, Guangyue-
dc.date.accessioned2024-09-28T00:30:17Z-
dc.date.available2024-09-28T00:30:17Z-
dc.date.issued2024-01-01-
dc.identifier.citationIEEE Transactions on Information Theory, 2024, v. 70, n. 1, p. 1-15-
dc.identifier.issn0018-9448-
dc.identifier.urihttp://hdl.handle.net/10722/347734-
dc.description.abstract— In this paper, we examine the Rényi entropy rate of stationary ergodic processes. For a special class of stationary ergodic processes, we prove that the Rényi entropy rate always exists and can be approximated by its defining sequence at most polynomially; moreover, using the Markov approximation method, we show that the Rényi entropy rate can be exponentially approximated by that of the Markov approximating sequence, as the Markov order goes to infinity. For the general case, by constructing a counterexample, we disprove the conjecture that the Rényi entropy rate of a general stationary ergodic process always converges to its Shannon entropy rate as α goes to 1.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers-
dc.relation.ispartofIEEE Transactions on Information Theory-
dc.subjectcutting-
dc.subjectergodic processes-
dc.subjecthidden Markov models-
dc.subjectRényi entropy rate-
dc.subjectstacking method-
dc.titleRényi Entropy Rate of Stationary Ergodic Processes -
dc.typeArticle-
dc.identifier.doi10.1109/TIT.2023.3318265-
dc.identifier.scopuseid_2-s2.0-85173050405-
dc.identifier.volume70-
dc.identifier.issue1-
dc.identifier.spage1-
dc.identifier.epage15-
dc.identifier.eissn1557-9654-
dc.identifier.issnl0018-9448-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats