Dynamical Systems Method for Solving Nonlinear Operator Equations - 1st Edition - ISBN: 9780444527950, 9780080465562

Dynamical Systems Method for Solving Nonlinear Operator Equations, Volume 208

1st Edition

Authors: Alexander Ramm
Hardcover ISBN: 9780444527950
eBook ISBN: 9780080465562
Imprint: Elsevier Science
Published Date: 25th September 2006
Page Count: 304
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Table of Contents

Preface Contents

  1. Introduction
  2. Ill-posed problems
  3. DSM for well-posed problems
  4. DSM and linear ill-posed problems
  5. Some inequalities
  6. DSM for monotone operators
  7. DSM for general nonlinear operator equations 8 DSM for operators satisfying a spectral assumption
  8. DSM in Banach spaces
    1. DSM and Newton-type methods without inversion of the derivative
    2. DSM and unbounded operators
    3. DSM and nonsmooth operators
    4. DSM as a theoretical tool
    5. DSM and iterative methods
    6. Numerical problems arising in applications
    7. Auxiliary results from analysis Bibliographical notes Bibliography Index


The book is of interest to graduate students in functional analysis, numerical analysis, and ill-posed and inverse problems especially. The book presents a general method for solving operator equations, especially nonlinear and ill-posed. It requires a fairly modest background and is essentially self-contained. All the results are proved in the book, and some of the background material is also included. The results presented are mostly obtained by the author.

Key Features

  • Contains a systematic development of a novel general method, the dynamical systems method, DSM for solving operator equations, especially nonlinear and ill-posed
  • Self-contained, suitable for wide audience
  • Can be used for various courses for graduate students and partly for undergraduates (especially for RUE classes)


Mathematicians, numerical analysists, specialists in scientific computing, engineers and others interested in solving operator equations, ill-posed and inverse problems.


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© Elsevier Science 2007
Elsevier Science
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About the Authors

Alexander Ramm Author

Affiliations and Expertise

Kansas State University, Manhattan, KS, USA