Analysis for Computer Scientists: Foundations, Methods, and Algorithms

Name: Analysis for Computer Scientists: Foundations, Methods, and Algorithms
Brand: Springer
SKU: 9783319911540
Price: 3639.0 INR
Availability: InStock

by Michael Oberguggenberger

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ISBN13: 9783319911540
Binding: Paperback
Subject: N/A
Publisher: Springer
Publisher Imprint: Springer
Publication Date: November 6, 2018
Pages: 378
Original Price: EUR 49.99
Language: English
Edition: 2018
Item Weight: 590 grams
BISAC Subject(s): Data Science / General, Counting & Numeration, and Applied

About The Book

From the Back Cover

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.

About The Author

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.

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