Optimum Quantization for Local Decision Based on Independent Samples

H. Vincent Poor, J. B. Thomas

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

The problem of designing quantizers for use in decision-making systems is considered. Applying the theory of local tests, general criteria are derived for the optimal selection of quantizer parameters for the large-sample-size case. These criteria agree with previously established results based on optimization in terms of distance measures and are shown also to lead to that quantizer-decision system which is most efficient asymptotically. To illustrate the design procedure, several applications to signal detection are discussed.

Original languageEnglish (US)
Pages (from-to)549-561
Number of pages13
JournalJournal of the Franklin Institute
Volume303
Issue number6
DOIs
StatePublished - Jun 1977

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Signal Processing
  • Computer Networks and Communications
  • Applied Mathematics

Fingerprint Dive into the research topics of 'Optimum Quantization for Local Decision Based on Independent Samples'. Together they form a unique fingerprint.

  • Cite this