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Guide to scientific computing in C++ / Joe Pitt-Francis; Jonathan Whiteley
Cham, Switzerland : Springer, 2017
293 pages. : illustrations
Ký hiệu phân loại (DDC): 005.133
This simple-to-follow textbook/reference provides an invaluable guide to object-oriented C++ programming for scientific computing. Through a series of clear and concise discussions, the key features most useful to the novice programmer are explored, enabling the reader to quickly master the basics and build the confidence to investigate less well-used features when needed. The text presents a hands-on approach that emphasizes the benefits of learning by example, stressing the importance of a clear programming style to minimise the introduction of errors into the code, and offering an extensive selection of practice exercises. This updated and enhanced new edition includes additional material on software testing, and on some new features introduced in modern C++ standards such as C++11. Topics and features: Presents a practical treatment of the C++ programming language for applications in scientific computing Reviews the essentials of procedural programming in C++, covering variables, flow of control, input and output, pointers, functions and reference variables Introduces the concept of classes, showcasing the main features of object-orientation, and discusses such advanced C++ features as templates and exceptions Examines the development of a collection of classes for linear algebra calculations, and presents an introduction to parallel computing using MPI Describes how to construct an object-oriented library for solving second order differential equations Contains appendices reviewing linear algebra and useful programming constructs, together with solutions to selected exercises Provides exercises and programming tips at the end of every chapter, and supporting code at an associated website This accessible textbook is a "must-read" for programmers of all levels of expertise. Basic familiarity with concepts such as operations between vectors and matrices, and the Newton-Raphson method for finding the roots of non-linear equations, would be an advantage, but extensive knowledge of the underlying mathematics is not assumed. Dr. Joe Pitt-Francis is a Departmental Lecturer at the Department of Computer Science and teaches Computer Science at Exeter College, the University of Oxford, UK. Prof. Jonathan Whiteley is Associate Professor at the Department of Computer Science and Governing Body Fellow of Linacre College, the University of Oxford, UK.
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Practical numerical and scientific computing with MATLAB® and Python / Eihab Bashier Mohammed Bashier
Boca Raton : CRC Press, 2020
xvii, 330 pages. : illustrations ; 25 cm.
Ký hiệu phân loại (DDC): 502.85
"This book concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems"
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Scientific computing with Matlab / Dingyü Xue; YangQuan Chen
Boca Raton, FL : CRC Press, 2016
586 pages. : illustrations ; 26 cm.
Ký hiệu phân loại (DDC): 502.85
"Scientific Computing with MATLAB®, Second Edition improves students’ ability to tackle mathematical problems. It helps students understand the mathematical background and find reliable and accurate solutions to mathematical problems with the use of MATLAB, avoiding the tedious and complex technical details of mathematics. This edition retains the structure of its predecessor Solving Applied Mathematical Problems with MATLAB® while expanding and updating the content of each chapter. Based on the authors’ extensive teaching, research, and industrial experiences, the text adheres to the following course sequence: •An overview of the computer languages suitable for mathematics •Fundamentals of MATLAB programming •Calculus problems •Linear algebra problems •Integral transforms and complex variable functions •Nonlinear equations and optimization problems •Differential equations problems •Data interpolation and functional approximation problems •Probability and statistics problems •Nontraditional methods, such as fuzzy logic, rough sets, neural networks, evolution algorithms, wavelets, and fractional calculus"
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