Scientific Computing: Vol. II – Eigenvalues and Optimization

Scientific Computing: Vol. II – Eigenvalues and Optimization Front Cover
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600 pages

Book Description

This is the second of three volumes providing a comprehensive presentation of the fundamentals of computing. This volume discusses more advanced topics than volume one, and is largely not a prerequisite for volume three. This book and its companions show how to determine the quality of computational results, and how to measure the relative efficiency of competing methods. Readers learn how to determine the maximum attainable accuracy of algorithms, and how to select the best method for computing problems. This book also discusses in several languages, including C++, Fortran and . There are 49 examples, 110 exercises, 66 algorithms, 24 interactive programs, 77 references to software programs and 1 case study.

Topics are introduced with goals, literature references and links to public software. There are descriptions of the current algorithms in LAPACK, GSLIB and MATLAB.

This book could be used for a second course in numerical methods, for either upper level undergraduates or first year graduate students. Parts of the text could be used for specialized courses, such as nonlinear optimization or iterative .

Table of Contents

Chapter 1 Eigenvalues And Eigenvectors
Chapter 2 Iterative Linear Algebra
Chapter 3 Nonlinear
Chapter 4 Constrained Optimization

Book Details

  • Title: Scientific Computing: Vol. II – Eigenvalues and Optimization
  • Author:
  • Length: 600 pages
  • Edition: 1st ed. 2017
  • Language: English
  • Publisher:
  • Publication Date: 2018-04-27
  • ISBN-10: 3319691066
  • ISBN-13: 9783319691060
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