Name: Analysis for Computer Scientists: Foundations, Methods, and Algorithms (Undergraduate Topics in Computer Science) (en Inglés)
SKU: 50885980
Price: 69.57 USD
Availability: InStock
Author: Michael Oberguggenberger
ISBN: 9783319911540

portada Analysis for Computer Scientists: Foundations, Methods, and Algorithms (Undergraduate Topics in Computer Science) (en Inglés)

Analysis for Computer Scientists: Foundations, Methods, and Algorithms (Undergraduate Topics in Computer Science) (en Inglés)

Formato

Libro Físico

Editorial

Springer

Autor

Michael Oberguggenberger

Año

2018

Idioma

Inglés

N° páginas

392

Encuadernación

Tapa Blanda

ISBN13

9783319911540

N° edición

Categorías

Ciencia y análisis de datos: generalidades
Análisis y captura de datos

Analysis for Computer Scientists: Foundations, Methods, and Algorithms (Undergraduate Topics in Computer Science) (en Inglés)

Michael Oberguggenberger (Autor) · Springer · Tapa Blanda

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Reseña del libro "Analysis for Computer Scientists: Foundations, Methods, and Algorithms (Undergraduate Topics in Computer Science) (en Inglés)"

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.