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Analysis for Computer Scientists

Foundations, Methods, and Algorithms

By Michael Oberguggenberger , Alexander Ostermann

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This textbook presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. It makes thorough use of examples and explanations using MATLAB, Maple and Java applets.

Full Description

  • ISBN13: 978-0-8572-9445-6
  • 356 Pages
  • User Level: Students
  • Publication Date: March 19, 2011
  • Available eBook Formats: PDF
  • eBook Price: $39.95
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Full Description
This textbook presents an algorithmic approach to mathematical analysis, with a focus on modelling and on the applications of analysis. Fully integrating mathematical software into the text as an important component of analysis, the book makes thorough use of examples and explanations using MATLAB, Maple, and Java applets. Mathematical theory is described alongside the basic concepts and methods of numerical analysis, supported by computer experiments and programming exercises, and an extensive use of figure illustrations. Features: thoroughly describes the essential concepts of analysis; provides summaries and exercises in each chapter, as well as computer experiments; discusses important applications and advanced topics; presents tools from vector and matrix algebra in the appendices, together with further information on continuity; includes definitions, propositions and examples throughout the text; supplementary software can be downloaded from the book’s webpage.
Table of Contents

Table of Contents

  1. Numbers.
  2. Real
  3. Valued Functions.
  4. Trigonometry.
  5. Complex Numbers.
  6. Sequences and Series.
  7. Limits and Continuity of Functions.
  8. The Derivative of a Function.
  9. Applications of the Derivative.
  10. Fractals and L
  11. Systems.
  12. Antiderivatives.
  13. Definite Integrals.
  14. Taylor Series.
  15. Numerical Integration.
  16. Curves.
  17. Scalar
  18. Valued Functions of Two Variables.
  19. Vector
  20. Valued Functions of Two Variables.
  21. Integration of Functions of Two Variables.
  22. Linear Regression.
  23. Differential Equations.
  24. Systems of Differential Equations.
  25. Numerical Solution of Differential Equations.
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