General formulas for the Neyman-Pearson type-II error exponent subject to fixed and exponential type-I error bounds

Po-Ning Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

The general formulas for the Neyman-Pearson type-II error exponent subject to two different type-I error constraints, as indicated in the title of the correspondence, are established. As revealed in the formulas, the type-II error exponents are fully determined by the ultimate statistical characteristic of the normalized log-likelihood ratio evaluated under the null hypothesis distribution. Applications of the general formulas to distributed Neyman-Pearson detection, and the channel reliability function are also demonstrated.

Original languageEnglish
Pages (from-to)316-323
Number of pages8
JournalIEEE Transactions on Information Theory
Volume42
Issue number1
DOIs
StatePublished - Jan 1996

Keywords

  • Channel reliability function
  • Distributed detection
  • Error exponent
  • Neyman-Pearson hypothesis testing

Fingerprint

Dive into the research topics of 'General formulas for the Neyman-Pearson type-II error exponent subject to fixed and exponential type-I error bounds'. Together they form a unique fingerprint.

Cite this