Authors:
- Easy-to-read mathematics with detailed explanations
- Demonstrates the transition of a mathematical problem to well-tested computer code in detail
- Uses modern Python-based programming tools and techniques
- Illustrates the computing pipeline: model, method, algorithm, implementation, testing, and visualization....
Part of the book series: Lecture Notes in Computational Science and Engineering (LNCSE, volume 110)
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Table of contents (5 chapters)
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Front Matter
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Back Matter
About this book
This text provides a very simple, initial introduction to the complete scientific computing pipeline: models, discretization, algorithms, programming, verification, and visualization. The pedagogical strategy is to use one case study – an ordinary differential equation describing exponential decay processes – to illustrate fundamental concepts in mathematics and computer science. The book is easy to read and only requires a command of one-variable calculus and some very basic knowledge about computer programming. Contrary to similar texts on numerical methods and programming, this text has a much stronger focus on implementation and teaches testing and software engineering in particular.
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Authors and Affiliations
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BioComp, Simula Research Laboratory BioComp, Lysaker, Norway
Hans Petter Langtangen
About the author
Bibliographic Information
Book Title: Finite Difference Computing with Exponential Decay Models
Authors: Hans Petter Langtangen
Series Title: Lecture Notes in Computational Science and Engineering
DOI: https://doi.org/10.1007/978-3-319-29439-1
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and the Author(s) 2016
Hardcover ISBN: 978-3-319-29438-4Published: 12 June 2016
Softcover ISBN: 978-3-319-80573-3Published: 30 May 2018
eBook ISBN: 978-3-319-29439-1Published: 10 June 2016
Series ISSN: 1439-7358
Series E-ISSN: 2197-7100
Edition Number: 1
Number of Pages: XIV, 200
Number of Illustrations: 29 b/w illustrations
Topics: Computational Science and Engineering, Programming Techniques, Software Engineering, Numerical and Computational Physics, Simulation, Mathematical and Computational Engineering