Least favorable additive noise under a divergence constraint

Andrew L. McKellips, Sergio Verdu

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

Abstract

An uncertainty class of additive noise probability density functions (pdfs) satisfying a constraint on divergence from a prescribed nominal is analyzed in the context of antipodal communication. From within this class, the noise pdf that maximizes detection error probability is determined for both zero-threshold and maximum-likelihood detection strategies. An optional additional constraint on SNR is also considered, and asymptotic behavior is studied for vanishing divergence tolerance.

Original languageEnglish (US)
Title of host publicationProceedings - 1997 IEEE International Symposium on Information Theory, ISIT 1997
Number of pages1
DOIs
StatePublished - Dec 1 1997
Event1997 IEEE International Symposium on Information Theory, ISIT 1997 - Ulm, Germany
Duration: Jun 29 1997Jul 4 1997

Publication series

NameIEEE International Symposium on Information Theory - Proceedings
ISSN (Print)2157-8095

Other

Other1997 IEEE International Symposium on Information Theory, ISIT 1997
CountryGermany
CityUlm
Period6/29/977/4/97

All Science Journal Classification (ASJC) codes

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

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