Signal Processing Filters Under Modeling Uncertainties.

Abstract

Matched and Wiener filters are considered for signal processing applications when the a priori information about signal and noise characteristics are not completely specified. The approach is to design filters which are saddle-point or max-min solutions for the criterion functional (mean-squared-error or signal-to-noise ratio) over the classes of allowable signal shapes and signal and noise spectral densities. Two-dimensional discrete-parameter processes are considered, and some numerical examples are presented. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1979
Accession Number
ADA080184

Entities

People

  • Leonard J. Cimini
  • Saleem A. Kassam
  • Tong Leong Lim

Organizations

  • Moore School of Electrical Engineering

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Air Force
  • Data Science
  • Distribution Functions
  • Electrical Engineering
  • Equations
  • Filters
  • Filtration
  • Frequency Response
  • Gaussian Distributions
  • Gaussian Processes
  • Matched Filters
  • Probability
  • Signal Detection
  • Signal Processing
  • Simultaneous Equations
  • Two Dimensional
  • Uncertainty

Fields of Study

  • Engineering

Readers

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