Optimum Quantization for Memoryless Detection in m-Dependent Noise,

Abstract

The problem of optimum data quantization for memoryless signal-detection systems operating in m-dependent noise environments is considered. The case where quantizer breakpoints are fixed or predetermined is considered first, and, for this case, existing results for general (unquantized) memoryless detection are modified to yield necessary and sufficient conditions for quantizer optimization in terms of asymptotic efficiency. Necessary conditions are also established for the optimum (asymptotically efficient) selection of quantizer breakpoints, and expressions are presented for the comparison of quantizer-detector performance on the basis of asymptotic relative efficiency. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1978
Accession Number
ADA055174

Entities

People

  • H. V. Poor
  • J. B. Thomas

Organizations

  • Princeton University

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Computer Science
  • Detection
  • Detectors
  • Distribution Functions
  • Efficiency
  • Electrical Engineering
  • Engineering
  • Environment
  • Equations
  • Gaussian Noise
  • Information Science
  • Optimization
  • Probability
  • Random Variables
  • Security
  • Signal Detection

Readers

  • Approximation Theory.
  • Regression Analysis.