Overview
- 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
Part of the book series: Undergraduate Topics in Computer Science (UTICS)
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Table of contents (21 chapters)
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Front Matter
Keywords
About this book
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.
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Authors and Affiliations
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
Book Title: Analysis for Computer Scientists
Book Subtitle: Foundations, Methods, and Algorithms
Authors: Michael Oberguggenberger, Alexander Ostermann
Series Title: Undergraduate Topics in Computer Science
DOI: https://doi.org/10.1007/978-3-319-91155-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Softcover ISBN: 978-3-319-91154-0Published: 06 November 2018
eBook ISBN: 978-3-319-91155-7Published: 24 October 2018
Series ISSN: 1863-7310
Series E-ISSN: 2197-1781
Edition Number: 2
Number of Pages: XII, 378
Number of Illustrations: 231 b/w illustrations
Topics: Math Applications in Computer Science, Computational Mathematics and Numerical Analysis, Mathematical and Computational Engineering, Discrete Mathematics in Computer Science