Alexander Ostermann

Diese grundlegende Einführung in die Analysis wendet sich an Informatiker im ersten Studienabschnitt. Um speziell auf die Bedürfnisse des Informatikstudiums einzugehen, haben die Autoren diesem Werk folgende Konzepte zugrunde gelegt: Algorithmischer Zugang, schlanke Darstellung, Software als integrativer Bestandteil, Betonung von Modellbildung und Anwendungen der Analysis. Der Gegenstand des Buches liegt im Spannungsfeld zwischen Mathematik, Informatik und Anwendungen. Hier kommt dem algorithmischen Denken ein hoher Stellenwert zu. Der gewählte Zugang beinhaltet: Entwicklung der Grundlagen der Analysis aus algorithmischer Sichtweise, Vergegenständlichung der Theorie mittels MATLAB- und Maple-Programmen und Java-Applets, Behandlung grundlegender Konzepte und Verfahren der numerischen Analysis. Das Buch kann ab dem ersten Semester als Vorlesungsgrundlage, als Begleittext zu einer Vorlesung oder im Selbststudium verwendet werden.

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.

In this textbook the authors present first-year geometry roughly in the order in which it was discovered. The first five chapters show how the ancient Greeks established geometry, together with its numerous practical applications, while more recent findings on Euclidian geometry are discussed as well. The following three chapters explain the revolution in geometry due to the progress made in the field of algebra by Descartes, Euler and Gauss. Spatial geometry, vector algebra and matrices are treated in chapters 9 and 10. The last chapter offers an introduction to projective geometry, which emerged in the 19thcentury. Complemented by numerous examples, exercises, figures and pictures, the book offers both motivation and insightful explanations, and provides stimulating and enjoyable reading for students and teachers alike.

In this textbook the authors present first-year geometry roughly in the order in which it was discovered. The first five chapters show how the ancient Greeks established geometry, together with its numerous practical applications, while more recent findings on Euclidian geometry are discussed as well. The following three chapters explain the revolution in geometry due to the progress made in the field of algebra by Descartes, Euler and Gauss. Spatial geometry, vector algebra and matrices are treated in chapters 9 and 10. The last chapter offers an introduction to projective geometry, which emerged in the 19thcentury. Complemented by numerous examples, exercises, figures and pictures, the book offers both motivation and insightful explanations, and provides stimulating and enjoyable reading for students and teachers alike.

Diese grundlegende Einführung in die Analysis wendet sich an Informatiker im ersten Studienabschnitt. Um speziell auf die Bedürfnisse des Informatikstudiums einzugehen, haben die Autoren diesem Werk folgende Konzepte zugrunde gelegt: Algorithmischer Zugang, schlanke Darstellung, Software als integrativer Bestandteil, Betonung von Modellbildung und Anwendungen der Analysis. Der Gegenstand des Buches liegt im Spannungsfeld zwischen Mathematik, Informatik und Anwendungen. Hier kommt dem algorithmischen Denken ein hoher Stellenwert zu. Der gewählte Zugang beinhaltet: Entwicklung der Grundlagen der Analysis aus algorithmischer Sichtweise, Vergegenständlichung der Theorie mittels MATLAB- und Maple-Programmen und Java-Applets, Behandlung grundlegender Konzepte und Verfahren der numerischen Analysis. Das Buch kann ab dem ersten Semester als Vorlesungsgrundlage, als Begleittext zu einer Vorlesung oder im Selbststudium verwendet werden.