Universal estimation of erasure entropy

Jiming Yu, Sergio Verdu

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

Erasure entropy rate differs from Shannon's entropy rate in that the conditioning occurs with respect to both the past and the future, as opposed to only the past (or the future). In this paper, consistent universal algorithms for estimating erasure entropy rate are proposed based on the basic and extended context-tree weighting (CTW) algorithms. Simulation results for those algorithms applied to Markov sources, tree sources, and English texts are compared to those obtained by fixed-order plug-in estimators with different orders.

Original languageEnglish (US)
Pages (from-to)350-357
Number of pages8
JournalIEEE Transactions on Information Theory
Volume55
Issue number1
DOIs
StatePublished - Jan 22 2009

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Computer Science Applications
  • Library and Information Sciences

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