Abstract
Recently, Samorodnitsky proved a strengthened version of Mrs. Gerber's Lemma, where the output entropy of a binary symmetric channel is bounded in terms of the average entropy of the input projected on a random subset of coordinates. Here, this result is applied for deriving novel lower bounds on the entropy rate of binary hidden Markov processes. For symmetric underlying Markov processes, our bound improves upon the best known bound in the very noisy regime. The nonsymmetric case is also considered, and explicit bounds are derived for Markov processes that satisfy the (1, ∞)-RLL constraint.
Original language | English |
---|---|
Title of host publication | Proceedings - ISIT 2016; 2016 IEEE International Symposium on Information Theory |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 690-694 |
Number of pages | 5 |
ISBN (Electronic) | 9781509018062 |
DOIs | |
State | Published - 10 Aug 2016 |
Externally published | Yes |
Event | 2016 IEEE International Symposium on Information Theory, ISIT 2016 - Barcelona, Spain Duration: 10 Jul 2016 → 15 Jul 2016 |
Publication series
Name | IEEE International Symposium on Information Theory - Proceedings |
---|---|
Volume | 2016-August |
ISSN (Print) | 2157-8095 |
Conference
Conference | 2016 IEEE International Symposium on Information Theory, ISIT 2016 |
---|---|
Country/Territory | Spain |
City | Barcelona |
Period | 10/07/16 → 15/07/16 |
Bibliographical note
Publisher Copyright:© 2016 IEEE.