Techniques for Accelerating Iterative Methods for the Solution of Mathematical Problems

Abstract

Mathematical problems can be solved numerically by deriving an iteration scheme that generates a sequence, the limit of which is the solution of the problem. However, quite often the generated sequence converges very slowly or even diverges. This study describes and compares methods designed to accelerate a slowly convergent sequence or to obtain the solution of the problem from a divergent sequence. The methods studied are Aitken's Delta-Squared method, Wynn's epsilon and modified epsilon methods, the minimal polynomial extrapolation method, the reduced rank extrapolation method, and Anderson's generalized secant algorithms. The derivation of these methods, as applied to both linear and nonlinear problems, are presented. In addition, the acceleration methods are compared theoretically and numerically. Results are presented from extensive numerical testing of problems in an m-dimensional vector space.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1989
Accession Number
ADA218272

Entities

People

  • Steven R. Capehart

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Air Force
  • Algorithms
  • Applied Mathematics
  • Complex Numbers
  • Differential Equations
  • Eigenvalues
  • Eigenvectors
  • Equations
  • Integral Equations
  • Linear Algebra
  • Linear Systems
  • New York
  • Numerical Analysis
  • Theorems
  • United States
  • Vector Spaces

Fields of Study

  • Mathematics

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Linear Algebra

Technology Areas

  • Space