Nonlinear Filtering Using Linear Combinations of Order Statistics.

Abstract

A nonlinear filter is considered whose output is given by a linear combination of the order statistics of the input samples. Assuming a constant signal in white noise, the coefficients are chosen to minimize the output MSE for several noise distributions. This new general filter is superior to both the median filter and the averaging filter, since they are just special cases. A class of heavy-tailed noise distributions is then considered, and optimal coefficients are found for various parameter values to determine the dependence of the filter coefficients on the heavy-tailedness (impulsivity) of the additive noise. Finally, some examples of designed filters are given operating on some simple inputs, and an examination of the root sets of the general filter is given. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1982
Accession Number
ADA124459

Entities

People

  • Alan Conrad Bovik

Organizations

  • University of Illinois Urbana–Champaign

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computational Science
  • Computations
  • Computer Simulations
  • Data Science
  • Distribution Functions
  • Electrical Engineering
  • Estimators
  • Information Science
  • New York
  • Normal Distribution
  • Numbers
  • Optimal Estimators
  • Order Statistics
  • Real Numbers
  • Statistical Analysis
  • Statistics

Fields of Study

  • Engineering

Readers

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