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  • © 2017

Scientific Computing

Vol. II - Eigenvalues and Optimization

  • Interactive HTML version uses 24 JavaScript programs for reader experimentation with algorithms
  • Combines analysis of well-posedness for scientific computing problems with perturbation analysis of related algorithms
  • Discusses the algorithms actually used by trusted software packages such as MATLAB, LAPACK and GSLIB

Part of the book series: Texts in Computational Science and Engineering (TCSE, volume 19)

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Table of contents (4 chapters)

  1. Front Matter

    Pages i-xxvi
  2. Eigenvalues and Eigenvectors

    • John A. Trangenstein
    Pages 1-201
  3. Iterative Linear Algebra

    • John A. Trangenstein
    Pages 203-305
  4. Nonlinear Systems

    • John A. Trangenstein
    Pages 307-432
  5. Constrained Optimization

    • John A. Trangenstein
    Pages 433-571
  6. Back Matter

    Pages 573-600

About this book

This is the second of three volumes providing a comprehensive presentation of the fundamentals of scientific 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 programming in several languages, including C++, Fortran and MATLAB. There are 49 examples, 110 exercises, 66 algorithms, 24 interactive JavaScript 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 innumerical 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 linear algebra.

Authors and Affiliations

  • Professor Emeritus of Mathematics, Department of Mathematics, Duke University, Durham, USA

    John A. Trangenstein

About the author

John Trangenstein is Professor of Mathematics Emeritus at Duke University in Durham North Carolina. He was a professor at Duke from 1991 to 2011. Previously he was a Mathematician in the Applied Mathematics Group at Lawrence Livermore National Laboratory from 1986 to 1991, a Research Specialist at Exxon Production Laboratory in Houston from 1981 to 1986, a Mathematician at S Cubed in San Diego from 1979 to 1981, and an Assistant Professor of Mathematics at the University of California at San Diego from 1975 to 1979. He received his PhD in Applied Mathematics from Cornell University in 1975, and his SB degree from the University of Chicago in 1972. He has authored two other book, with Cambridge University Press, namely Numerical Solution of Hyperbolic Partial Differential Equations (2009) and Numerical Solution of Elliptic and Parabolic Partial Differential Equations (2013).


Bibliographic Information

Buy it now

Buying options

eBook USD 29.99 USD 54.99
45% discount Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 39.99 USD 69.99
43% discount Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 49.99 USD 99.99
50% discount Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access