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Scientific Computing - An Introduction using Maple and MATLAB
(Englisch)
Texts in Computational Science and Engineering 11
Walter Gander & Martin J. Gander & Felix Kwok

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Scientific Computing - An Introduction using Maple and MATLAB

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  • Springer Basel AG
    Picassoplatz 4
    CH-4010 Basel
    +41 61 2050707
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  • 34864765

Produktbeschreibung

Equal emphasis on theory, symbolic computation and numerical algorithms
Numerous complete, ready-to-run programs in Matlab and Maple, complete with many examples
In-depth treatment of many advanced topics, beyond standard undergraduate texts


Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple – Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material "hands-on”.
Why Study Scientific Computing?.- Finite Precision Arithmetic.- Linear Systems of Equations.- Interpolation.- Nonlinear Equations.-Least Squares Problems.- Eigenvalue Problems.- Differentiation.- Quadrature.- Numerical Ordinary Differential Equations.- Iterative Methods for Linear Systems.- Optimization.- Bibliography.- Index.

From the book reviews:

"This is an elaborate book on fundamental numerical methods including numerical ordinary differential equations and optimization. ... All chapters are organized in the same nice way by beginning with an introductary example and ending with a large number of exercises. The presentation of the material is reader orientated such that e.g. a student can learn directly from the book. Many details are given and special attention lies on various numerical calculations which enlight the performance of the respective algorithms.” (Rolf Dieter Grigorieff, zbMATH, Vol. 1296, 2014)
This book offers an introduction to the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes. Includes numerous complete, ready-to-run programs in Matlab and Maple.
Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple - Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material "hands-on".
Why Study Scientific Computing?.- Finite Precision Arithmetic.- Linear Systems of Equations.- Interpolation.- Nonlinear Equations.-Least Squares Problems.- Eigenvalue Problems.- Differentiation.- Quadrature.- Numerical Ordinary Differential Equations.- Iterative Methods for Linear Systems.- Optimization.- Bibliography.- Index.

From the book reviews:

"This is an elaborate book on fundamental numerical methods including numerical ordinary differential equations and optimization. ... All chapters are organized in the same nice way by beginning with an introductary example and ending with a large number of exercises. The presentation of the material is reader orientated such that e.g. a student can learn directly from the book. Many details are given and special attention lies on various numerical calculations which enlight the performance of the respective algorithms." (Rolf Dieter Grigorieff, zbMATH, Vol. 1296, 2014)

Inhaltsverzeichnis

Why Study Scientific Computing?.- Finite Precision Arithmetic.- Linear Systems of Equations.- Interpolation.- Nonlinear Equations.-Least Squares Problems.- Eigenvalue Problems.- Differentiation.- Quadrature.- Numerical Ordinary Differential Equations.- Iterative Methods for Linear Systems.- Optimization.- Bibliography.- Index.


Klappentext

Scientific computing is the study of how to use computers effectively to solve problems that arise from the mathematical modeling of phenomena in science and engineering. It is based on mathematics, numerical and symbolic/algebraic computations and visualization. This book serves as an introduction to both the theory and practice of scientific computing, with each chapter presenting the basic algorithms that serve as the workhorses of many scientific codes; we explain both the theory behind these algorithms and how they must be implemented in order to work reliably in finite-precision arithmetic. The book includes many programs written in Matlab and Maple - Maple is often used to derive numerical algorithms, whereas Matlab is used to implement them. The theory is developed in such a way that students can learn by themselves as they work through the text. Each chapter contains numerous examples and problems to help readers understand the material "hands-on".


Equal emphasis on theory, symbolic computation and numerical algorithms

Numerous complete, ready-to-run programs in Matlab and Maple, complete with many examples

In-depth treatment of many advanced topics, beyond standard undergraduate texts

Includes supplementary material: sn.pub/extras



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