Time Constants and Learning Curves of LMS Adaptive Filters.

Abstract

This paper treats the convergence of adaptive LMS filters and, in particular, the adaptive line enhancer (ALE). The learning curves of such a filter are a sum of exponentially decaying modes with time constants given by the eigenvalues of the input correlation matrix and the relative initial magnitudes given by the projections of the filter on the eigenvectors. It is shown that, for large filter lengths, a simple correspondence may be set up between the discrete and continuous cases. Indexed by frequency, the eigenvalues of the correlation matrix correspond to the magnitude of the power spectrum, and the projections onto the eigenvectors to the filter transfer function. A detailed analysis is carried out for single pole spectra and evaluated through a computer simulation. In general, the techniques developed provide a physical context, i.e., the signal spectrum, in which to evaluate convergence. Thus, it is possible, with varying degrees of accuracy depending on knowledge of the input spectrum, to predict the convergence behavior of the system in general. (Author)

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Document Details

Document Type
Technical Report
Publication Date
Nov 01, 1978
Accession Number
ADA063317

Entities

People

  • M. Shensa

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Accuracy
  • Adaptive Filters
  • Bandwidth
  • Computational Science
  • Computer Simulations
  • Computers
  • Digital Signal Processing
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Frequency
  • Numerical Analysis
  • Power Spectra
  • Signal Processing
  • Simulations
  • Transfer Functions
  • White Noise

Fields of Study

  • Engineering

Readers

  • Calculus or Mathematical Analysis
  • Computational Modeling and Simulation
  • Phased Array Antenna Design.