Finite-memory hypothesis testing with semi-bounded likelihood ratio

Jack Koplowitz, Sanjeev R. Kulkarni

Research output: Contribution to conferencePaper

Abstract

We consider hypothesis testing with a finite memory when the likelihood ratio is semi-bounded. It is shown that a 2-state memory can achieve correct convergence with probability one under one hypothesis but only in probability under the other hypothesis.

Original languageEnglish (US)
Number of pages1
StatePublished - Jan 1 1997
Externally publishedYes
EventProceedings of the 1997 IEEE International Symposium on Information Theory - Ulm, Ger
Duration: Jun 29 1997Jul 4 1997

Other

OtherProceedings of the 1997 IEEE International Symposium on Information Theory
CityUlm, Ger
Period6/29/977/4/97

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering
  • Applied Mathematics
  • Modeling and Simulation
  • Theoretical Computer Science
  • Information Systems

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  • Cite this

    Koplowitz, J., & Kulkarni, S. R. (1997). Finite-memory hypothesis testing with semi-bounded likelihood ratio. Paper presented at Proceedings of the 1997 IEEE International Symposium on Information Theory, Ulm, Ger, .