The Common Thread in Optimal Adaptive Non Recursive Filters.

Abstract

Filters are applied to time sequences to extract desired signals from random noise and from interfering signals. The specific form of the filter is related to apriori knowledge of the statistics of the desired and the undesired signals. Classic filter design entails two distinct stages. The first is to employ some monitoring and smoothing scheme which will lead to estimates of the signal statistics such as the signal and noise covariance functions or power spectrums. The second stage is to formulate the filter response in terms of these estimated statistics. In this paper we review a class of filters for which the two stages just described are performed simultaneously and iteratively. The filter coefficients are changed by a recursive algorithm which corrects the filter response during the processing of the input data. The capability to modify the filter response during operation makes it possible to track and to filter signals with slowly changing statistics. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Aug 04, 1981
Accession Number
ADA122850

Entities

People

  • Frederick J. Harris

Organizations

  • San Diego State University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Adaptive Filters
  • Algorithms
  • Classification
  • Computations
  • Convergence
  • Coordinate Systems
  • Covariance
  • Data Science
  • Difference Equations
  • Eigenvalues
  • Equations
  • Filters
  • Information Science
  • Mathematical Filters
  • Recursive Filters
  • Statistics
  • Steady State

Fields of Study

  • Engineering

Readers

  • Image Processing and Computer Vision.
  • Radar Systems Engineering.
  • Statistical inference.