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Titlebook: Analysis for Computer Scientists; Foundations, Methods Michael Oberguggenberger,Alexander Ostermann Textbook 2018Latest edition Springer Na

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發(fā)表于 2025-3-21 17:43:40 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Analysis for Computer Scientists
期刊簡稱Foundations, Methods
影響因子2023Michael Oberguggenberger,Alexander Ostermann
視頻videohttp://file.papertrans.cn/157/156299/156299.mp4
發(fā)行地址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 a
學(xué)科分類Undergraduate Topics in Computer Science
圖書封面Titlebook: Analysis for Computer Scientists; Foundations, Methods Michael Oberguggenberger,Alexander Ostermann Textbook 2018Latest edition Springer Na
影響因子.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
Pindex Textbook 2018Latest edition
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發(fā)表于 2025-3-22 00:00:43 | 只看該作者
Alexander Godulla,Cornelia Wolfeir investigation are at the core of analysis. They help to model dependencies of variable quantities, from simple planar graphs, curves and surfaces in space to solutions of differential equations or the algorithmic construction of fractals. One the one hand, this chapter serves to introduce the ba
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Maria Schwartz,Meike Neuhaus,Samuel Ulbrichtp of complex functions transformations of the plane can be expressed, solution formulas for differential equations can be obtained, and matrices can be classified. Not least, fractals can be defined by complex iteration processes. In this section we introduce complex numbers and then discuss some el
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發(fā)表于 2025-3-22 08:58:52 | 只看該作者
Social Media. Alltag, Daten und Gesellschaftinuity, differentiability, series expansions of functions, integration, etc. The transition from the . to the . constitutes the modelling strength of mathematical analysis. Discrete models of physical, technical or economic processes can often be better and easily understood, provided that the numbe
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Digitale Lernangebote in der Pflegeays be joined by a secant, which is a good model for the tangent whenever these points are close to each other. In a limiting process, the secant (discrete model) is replaced by the tangent (continuous model). Differential calculus, which is based on this limiting process, has become one of the most
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發(fā)表于 2025-3-23 08:02:43 | 只看該作者
Dorothee M. Meister,Anna-Maria Kaminon we discuss the approximation of a function by Taylor polynomials and by Taylor series in this chapter. As important applications we will use Taylor series to compute limits of functions and to analyse various approximation formulas.
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