Asymptotically Optimum Zero Memory Detectors for Dependent Noise Process.

Abstract

Design of detectors for known signals in non-Gaussian PH1-mixing noise is considered. Applying the criterion of asymptotic relative efficiency, the design of the optimal memoryless detector is specified and is seen to depend only on second-order statistical knowledge of the noise. It is then shown that in many cases this design reduces to approximating the noise process with an m-dependent processs and obtaining the optimal nonlinearity through a limiting process. In addition, conditions are given for the existence of a unique optimal nonlinearity. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA069982

Entities

People

  • D. R. Halverson
  • G. L. Wise

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Detection
  • Detectors
  • Eigenvalues
  • Electrical Engineering
  • Engineering
  • Equations
  • Inequalities
  • Information Science
  • Integral Equations
  • New York
  • Noise
  • Probability
  • Random Variables
  • Scientific Research
  • Sequences
  • Triangles
  • White Noise

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Statistical inference.