Iterative System Modeling Using Multigrid Techniques

Abstract

One and two-dimensional system identification and modeling algorithms utilizing multigrid techniques are presented. Finite impulse response (FIR), autoregressive (AR), infinite impulse response (IIR), and 2-D block matrix iterative system modeling algorithms are enhanced and made more efficient using the multigrid methods. The convergence performance of these algorithms is improved with the multigrid techniques. The reduction in the number of iterations required to converge to a solution is realized by forcing the low frequency error components to appear to be at a higher frequency by transferring to a coarser sampling period. Performance comparisons are presented for FIR, AR, IIR, and 2-D block matrix modeling simulations with and without the multigrid- techniques employed.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA245522

Entities

People

  • Dean A. Richter

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Classification
  • Computational Complexity
  • Computational Science
  • Computers
  • Convergence
  • Cross Correlation
  • Digital Signal Processing
  • Electrical Engineering
  • Engineering
  • Frequency
  • Frequency Response
  • Iterations
  • Sampling
  • Simulations
  • Two Dimensional
  • United States

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Linear Algebra
  • Radio communications and signal processing.