Solving Large and Dense Eigenvalue Problems that Arise in Physics.

Abstract

We worked on a fundamental problem of decomposing a signal into a small set of decaying complex exponentials. This problem arises in a wide range of disciplines, including nuclear magnetic resonance, speech processing and system identification. We developed a new class of numerical algorithms, and gave a simple, purely linear algebraic proof on why our new approach works. Our class contains two arbitrary matrice F and G. Specific choices of these two matrices result in Prony's and Kung's methods. So all our theoretical results cover the two procedures. This advance is important, for Kung's proof can be difficult to digest. Other choices of F and G give rise to new methods with other desirable characteristics; e.g., our new Hankel QRD method is about ten times faster than Kung's scheme, also known as the Hankel SVD method. Another attraction of the QRD approach is that it is easily updatable to accommodate new data, which is not so for an SVD technique.

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Document Details

Document Type
Technical Report
Publication Date
Mar 18, 1996
Accession Number
ADA310880

Entities

People

  • Franklin T. Luk

Organizations

  • Rensselaer Polytechnic Institute

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Algorithms
  • Availability
  • Classification
  • Computer Science
  • Decomposition
  • Eigenvalues
  • Equations
  • Identification
  • Least Squares Method
  • Magnetic Resonance
  • Military Research
  • Nuclear Magnetic Resonance
  • Optical Scanning
  • Polynomials
  • Security
  • Technical Information Centers

Fields of Study

  • Mathematics

Readers

  • Approximation Theory.
  • Linear Algebra
  • Technical Research and Report Writing.