Small-sample distribution estimation over sticky channels

Farzad Famoud, Olgica Milenkovic, Narayana Prasad Santhanam

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We consider the problem of estimating unknown source distributions based on a small num ber of possibly erroneous observations. Errors are modeled as arising from sticky channels, which introduce repetitions of transmitted source symbols. Both the problems of estimating the distribution for known and unknown channel parameters are considered. We propose three heuristic algorithms and a method based on ExpectationMaximization for solving the problem. These algorithms represent a combination of iterative optimization techniques and Good-Turing estimators.

Original languageEnglish (US)
Title of host publication2009 IEEE International Symposium on Information Theory, ISIT 2009
Pages1125-1129
Number of pages5
DOIs
StatePublished - Nov 19 2009
Event2009 IEEE International Symposium on Information Theory, ISIT 2009 - Seoul, Korea, Republic of
Duration: Jun 28 2009Jul 3 2009

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8102

Other

Other2009 IEEE International Symposium on Information Theory, ISIT 2009
Country/TerritoryKorea, Republic of
CitySeoul
Period6/28/097/3/09

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'Small-sample distribution estimation over sticky channels'. Together they form a unique fingerprint.

Cite this