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NLSE: Parameter-Based Inversion Algorithm

  • Harold A. Sabbagh
  • R. Kim Murphy
  • Elias H. Sabbagh
  • John C. Aldrin
  • Jeremy S. Knopp
Part of the Scientific Computation book series (SCIENTCOMP)

Abstract

Chapter 11 introduced us to the notion of an inverse problem and gave us some examples of the value of this idea to the solution of realistic industrial problems. The basic inversion algorithm described in Chap. 11 was based upon the Gauss–Newton theory of nonlinear least-squares estimation and is called NLSE in this book. In this chapter we will develop the mathematical background of this theory more fully, because this algorithm will be the foundation of inverse methods and their applications during the remainder of this book. We hope, thereby, to introduce the reader to the application of sophisticated mathematical concepts to engineering practice without introducing excessive mathematical sophistication.

Keywords

Inverse Problem Singular Value Decomposition Nondestructive Evaluation Fisher Information Inverse Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Harold A. Sabbagh
    • 1
  • R. Kim Murphy
    • 1
  • Elias H. Sabbagh
    • 1
  • John C. Aldrin
    • 2
  • Jeremy S. Knopp
    • 3
  1. 1.Victor Technologies, LLCBloomingtonUSA
  2. 2.Computational ToolsGurneeUSA
  3. 3.Air Force Research Laboratory (AFRL/RXLP)Wright-Patterson AFBUSA

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