Asymptotic Error Probability of Binary Hypothesis Testing for Poisson Point-Process Observations

Sergio Verdú

Research output: Contribution to journalArticle

12 Scopus citations

Abstract

It is shown that the asymptotic probability of error of a binary equiprobable hypothesis test for observed Poisson point processes with rates [formula omited] is equal to the error probability of optimum deterministic-signal detection in additive white Gaussian noise when the signals coincide with the square roots of the point-process rates. The implication of this result in the error rate analysis of optical digital communication systems is discussed.

Original languageEnglish (US)
Pages (from-to)113-115
Number of pages3
JournalIEEE Transactions on Information Theory
Volume32
Issue number1
DOIs
StatePublished - Jan 1986

All Science Journal Classification (ASJC) codes

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

Fingerprint Dive into the research topics of 'Asymptotic Error Probability of Binary Hypothesis Testing for Poisson Point-Process Observations'. Together they form a unique fingerprint.

  • Cite this