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© 2018

Analysis for Computer Scientists

Foundations, Methods, and Algorithms

  • Presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis

  • Makes thorough use of examples and explanations using MATLAB, Maple, and Java applets

  • Describes mathematical theory alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises

Textbook

Part of the Undergraduate Topics in Computer Science book series (UTICS)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Michael Oberguggenberger, Alexander Ostermann
    Pages 1-12
  3. Michael Oberguggenberger, Alexander Ostermann
    Pages 13-25
  4. Michael Oberguggenberger, Alexander Ostermann
    Pages 27-37
  5. Michael Oberguggenberger, Alexander Ostermann
    Pages 39-47
  6. Michael Oberguggenberger, Alexander Ostermann
    Pages 49-67
  7. Michael Oberguggenberger, Alexander Ostermann
    Pages 69-79
  8. Michael Oberguggenberger, Alexander Ostermann
    Pages 81-103
  9. Michael Oberguggenberger, Alexander Ostermann
    Pages 105-121
  10. Michael Oberguggenberger, Alexander Ostermann
    Pages 123-138
  11. Michael Oberguggenberger, Alexander Ostermann
    Pages 139-147
  12. Michael Oberguggenberger, Alexander Ostermann
    Pages 149-163
  13. Michael Oberguggenberger, Alexander Ostermann
    Pages 165-174
  14. Michael Oberguggenberger, Alexander Ostermann
    Pages 175-184
  15. Michael Oberguggenberger, Alexander Ostermann
    Pages 185-207
  16. Michael Oberguggenberger, Alexander Ostermann
    Pages 209-230
  17. Michael Oberguggenberger, Alexander Ostermann
    Pages 231-239
  18. Michael Oberguggenberger, Alexander Ostermann
    Pages 241-254
  19. Michael Oberguggenberger, Alexander Ostermann
    Pages 255-273
  20. Michael Oberguggenberger, Alexander Ostermann
    Pages 275-295

About this book

Introduction

This easy-to-follow textbook/reference presents a concise introduction to mathematical analysis from an algorithmic point of view, with a particular focus on applications of analysis and aspects of mathematical modelling. The text describes the mathematical theory alongside the basic concepts and methods of numerical analysis, enriched by computer experiments using MATLAB, Python, Maple, and Java applets. This fully updated and expanded new edition also features an even greater number of programming exercises.

Topics and features:

  • Describes the fundamental concepts in analysis, covering real and complex numbers, trigonometry, sequences and series, functions, derivatives, integrals, and curves
  • Discusses important applications and advanced topics, such as fractals and L-systems, numerical integration, linear regression, and differential equations
  • Presents tools from vector and matrix algebra in the appendices, together with further information on continuity
  • Includes added material on hyperbolic functions, curves and surfaces in space, second-order differential equations, and the pendulum equation (NEW)
  • Contains experiments, exercises, definitions, and propositions throughout the text
  • Supplies programming examples in Python, in addition to MATLAB (NEW)
  • Provides supplementary resources at an associated website, including Java applets, code source files, and links to interactive online learning material

Addressing the core needs of computer science students and researchers, this clearly written textbook is an essential resource for undergraduate-level courses on numerical analysis, and an ideal self-study tool for professionals seeking to enhance their analysis skills.

Dr. Michael Oberguggenberger is a professor in the Unit of Engineering Mathematics at the University of Innsbruck, Austria. Dr. Alexander Ostermann is a professor in the Department of Mathematics at the University of Innsbruck, Austria.

Keywords

Algorithms Analysis Computer Science MATLAB Maple Numerical Mathematics

Authors and affiliations

  1. 1.University of InnsbruckInnsbruckAustria
  2. 2.University of InnsbruckInnsbruckAustria

About the authors

Dr. Michael Oberguggenberger is a professor in the Unit of Engineering Mathematics at the University of Innsbruck, Austria.

Dr. Alexander Ostermann is a professor in the Department of Mathematics at the University of Innsbruck, Austria.

Bibliographic information

Industry Sectors
Engineering

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