Non-Linear Effects in Adaptive Linear Prediction

Abstract

When a conventional NLMS adaptive filter is used to predict a process, especially when predicting several samples ahead, non-linear effects can be observed. These non-linear effects produce adaptive filter performance that exceeds that of the conventional Wiener filter, and engenders weight behavior that is of a time-varying nature. After showing the existence of such non-linear effects, we show their relation to the difference between the structure of the optimal predictor and the structure used to model the data to be predicted. The nonlinear effects are stronger when the process to be predicted is more narrowband.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2002
Accession Number
ADA506903

Entities

People

  • A. A. Beex
  • James R. Zeidler

Organizations

  • Naval Information Warfare Systems Command

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Adaptive Filters
  • Algorithms
  • Bandwidth
  • Delay Lines
  • Department Of Defense
  • Estimators
  • Filters
  • Filtration
  • Image Processing
  • Information Processing
  • Iterations
  • Narrowband
  • Noise
  • Optimal Estimators
  • Steady State
  • United States Government
  • White Noise

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Theoretical Analysis.