Schemes for bidirectional modeling of discrete stationary sources

Jiming Yu, Sergio Verdú

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

We develop adaptive schemes for bidirectional modeling of unknown discrete stationary sources. These algorithms can be applied to statistical inference problems such as noncausal universal discrete denoising that exploit bidirectional dependencies. Efficient algorithms for constructing those models are developed and we compare their performance to that of the DUDE algorithm for universal discrete denoising.

Original languageEnglish (US)
Pages (from-to)4789-4807
Number of pages19
JournalIEEE Transactions on Information Theory
Volume52
Issue number11
DOIs
StatePublished - Nov 1 2006

All Science Journal Classification (ASJC) codes

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

Keywords

  • Bidirectional modeling
  • Discrete stationary sources
  • Universal algorithms
  • Universal discrete denoising

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