Author: Brian Hilton Flowers,Sir Brian Hilton Flowers

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### An Introduction to Numerical Methods in C++

Designed for the many applied mathematicians and engineers who wish to explore computerized numerical methods, this text explores the power of C++ as a tool for work in numerical methods. This revision of the successful first edition includes for the first time information on programming in Windows-based environments. In addition it includes new topics and methods throughout the text that clarify and enhance the treatment of the subject.

### An Introduction to Programming and Numerical Methods in MATLAB

The material presented in this volume provides an introduction to the numerical methods that are typically encountered and used in undergraduate science and engineering courses, and is developed in tandem with MATLAB, which allows rapid prototyping and testing of the methods.

### An Introduction to MATLAB® Programming and Numerical Methods for Engineers

Assuming no prior background in linear algebra or real analysis, An Introduction to MATLAB® Programming and Numerical Methods for Engineers enables you to develop good computational problem solving techniques through the use of numerical methods and the MATLAB® programming environment. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level allowing you to quickly apply results in practical settings. Tips, warnings, and "try this" features within each chapter help the reader develop good programming practices Chapter summaries, key terms, and functions and operators lists at the end of each chapter allow for quick access to important information At least three different types of end of chapter exercises — thinking, writing, and coding — let you assess your understanding and practice what you've learned

### Numerical Methods in Finance with C++

Provides aspiring quant developers with the numerical techniques and programming skills needed in quantitative finance. No programming background required.

### Introduction to Numerical Analysis

An Introduction to Numerical Analysis is designed for a first course on numerical analysis for students of Science and Engineering including Computer Science. The text contains derivation of algorithms for solving engineering and science problems and also deals with error analysis. It has numerical examples suitable for solving through computers. The special features are comparative efficiency and accuracy of various algorithms due to finite digit arithmetic used by the computers.

### Introduction to Numerical Programming

Makes Numerical Programming More Accessible to a Wider Audience Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity. Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning. Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.

### C Programming and Numerical Analysis

This book is aimed at those in engineering/scientific fields who have never learned programming before but are eager to master the C language quickly so as to immediately apply it to problem solving in numerical analysis. The book skips unnecessary formality but explains all the important aspects of C essential for numerical analysis. Topics covered in numerical analysis include single and simultaneous equations, differential equations, numerical integration, and simulations by random numbers. In the Appendices, quick tutorials for gnuplot, Octave/MATLAB, and FORTRAN for C users are provided.

### Computing for Numerical Methods Using Visual C++

A visual, interdisciplinary approach to solving problems in numerical methods Computing for Numerical Methods Using Visual C++ fills the need for a complete, authoritative book on the visual solutions to problems in numerical methods using C++. In an age of boundless research, there is a need for a programming language that can successfully bridge the communication gap between a problem and its computing elements through the use of visual-ization for engineers and members of varying disciplines, such as biologists, medical doctors, mathematicians, economists, and politicians. This book takes an interdisciplinary approach to the subject and demonstrates how solving problems in numerical methods using C++ is dominant and practical for implementation due to its flexible language format, object-oriented methodology, and support for high numerical precisions. In an accessible, easy-to-follow style, the authors cover: Numerical modeling using C++ Fundamental mathematical tools MFC interfaces Curve visualization Systems of linear equations Nonlinear equations Interpolation and approximation Differentiation and integration Eigenvalues and Eigenvectors Ordinary differential equations Partial differential equations This reader-friendly book includes a companion Web site, giving readers free access to all of the codes discussed in the book as well as an equation parser called "MyParser" that can be used to develop various numerical applications on Windows. Computing for Numerical Methods Using Visual C++ serves as an excellent reference for students in upper undergraduate- and graduate-level courses in engineering, science, and mathematics. It is also an ideal resource for practitioners using Microsoft Visual C++.

### Numerical Methods in 'C'

### Numerical Methods with C++ Programming

The rapid development of high speed digital computers and the increasing desire for numerical answers to applied problems have led to increased demands in the courses dealing with the methods and techniques of numerical analysis. Numerical methods have always been useful but their role in the present-day scientific research has become prominent. For example, they enable one to find the roots of transcendental equations and in solving nonlinear differential equations. Indeed, they give the solution when ordinary analytical methods fail. This well-organized and comprehensive text aims at enhancing and strengthening numerical methods concepts among students using C++ programming, a fast emerging preferred programming language among software developers. The book provides an synthesis of both theory and practice. It focuses on the core areas of numerical analysis including algebraic equations, interpolation, boundary value problem, and matrix eigenvalue problems. The mathematical concepts are supported by a number of solved examples. Extensive self-review exercises and answers are provided at the end of each chapter to help students review and reinforce the key concepts. KEY FEATURES : C++ programs are provided for all numerical methods discussed. More than 400 unsolved problems and 200 solved problems are included to help students test their grasp of the subject. The book is intended for undergraduate and postgraduate students of Mathematics, Engineering and Statistics. Besides, students pursuing BCA and MCA and having Numerical Methods with C++ Programming as a subject in their course will benefit from this book.

### An Introduction to Numerical Analysis

Introduction to numerical analysis combining rigour with practical applications. Numerous exercises plus solutions.

### Numerical Methods in Engineering with Python 3

Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.

### NUMERICAL ANALYSIS WITH ALGORITHMS AND COMPUTER PROGRAMS IN C++

This concise introduction to Numerical Methods blends the traditional algebraic approach with the computer-based approach, with special emphasis on evolving algorithms which have been directly transformed into programs in C++. Each numerical method used for solving nonlinear algebraic equations, simultaneous linear equations, differentiation, integration, ordinary differential equations, curve-fitting, etc. is accompanied by an algorithm and the corresponding computer program. All computer programs have been test run on Linux ‘Ubuntu C++’ as well as Window-based ‘Dev C++’, Visual C++ and ‘Turbo C++’ compiler systems. Since different types of C++ compilers are in use today, instructions have been given with each computer program to run it on any kind of compiler. To this effect, an introductory chapter on C++ compilers has been added for ready reference by the students and teachers. Another major feature of the book is the coverage of the practicals prescribed for laboratory work in Numerical Analysis. Each chapter has a large number of laboratory tested programming examples and exercises including questions from previous years’ examinations. This textbook is intended for the undergraduate science students pursuing courses in BSc (Hons.) Physics, BSc (Hons.) Electronics and BSc (Hons.) Mathematics. It is also suitable for courses on Numerical Analysis prescribed for the engineering students of all disciplines.

### An Introduction to C++ and Numerical Methods

An introduction to C++ providing explanations of the basics of numerical methods, scientific computing and the basic constructs of C++. Subsequent chapters revisit these topics to treat them in more detail. It also covers numerical methods used in scientific and engineering computation.

### An Introduction to Numerical Methods and Analysis

### Numerical Methods in Engineering and Science

This comprehensive text is an excellent resource for students and practicing engineers. Providing an excellent balance of theoretical and applied topics, it shows the numerical methods used with C, C++, and MATLAB.

### Solving PDEs in C++

This comprehensive book not only introduces the C and C++ programming languages but also shows how to use them in the numerical solution of partial differential equations (PDEs). It leads the reader through the entire solution process, from the original PDE, through the discretization stage, to the numerical solution of the resulting algebraic system. The well-debugged and tested code segments implement the numerical methods efficiently and transparently. Basic and advanced numerical methods are introduced and implemented easily and efficiently in a unified object-oriented approach.The high level of abstraction available in C++ is particularly useful in the implementation of complex mathematical objects, such as unstructured mesh, sparse matrix, and multigrid hierarchy, often used in numerical modeling. This book introduces a unified approach for the implementation of these objects. The code segments and their detailed explanations clearly show how easy it is to implement advanced algorithms in C++. Solving PDEs in C++ contains all the required background in programming, PDEs, and numerical methods; only an elementary background in linear algebra and calculus is required. Useful exercises and solutions conclude each chapter. For the more advanced reader, there is also material on stability analysis and weak formulation. The final parts of the book demonstrate the object-oriented approach in advanced applications.The book is written for researchers, engineers, and advanced students who wish to increase their familiarity with numerical methods and to implement them in modern programming tools. Solving PDEs in C++ can be used as a textbook in courses in C++ with applications, C++ in engineering, numerical analysis, and numerical PDEs at the advanced undergraduate and graduate levels. Because it is self-contained, the book is also suitable for self-study by researchers and students in applied and computational science and engineering. Contents List of Figures; List of Tables; Preface; Part I: Programming. Chapter 1: Introduction to C; Chapter 2: Introduction to C++; Chapter 3: Data Structures; Part II: The Object-Oriented Approach. Chapter 4: Object-Oriented Programming; Chapter 5: Algorithms and Their Object-Oriented Implementation; Chapter 6: Object-Oriented Analysis; Part III: Partial Differential Equations and Their Discretization. Chapter 7: The Convection-Diffusion Equation; Chapter 8: Stability Analysis 209; Chapter 9: Nonlinear Equations; Chapter 10: Application in Image Processing; Part IV: The Finite-Element Discretization Method. Chapter 11: The Weak Formulation; Chapter 12: Linear Finite Elements; Chapter 13: Unstructured Finite-Element Meshes; Chapter 14: Adaptive Mesh Refinement; Chapter 15: High-Order Finite Elements; Part V: The Numerical Solution of Large Sparse Linear Systems of Equations. Chapter 16: Sparse Matrices and Their Implementation; Chapter 17: Iterative Methods for Large Sparse Linear Systems; Chapter 18: Parallelism; Part VI: Applications. Chapter 19: Diffusion Equations; Chapter 20: The Linear Elasticity Equations; Chapter 21: The Stokes Equations; Chapter 22: Electromagnetic Waves; Appendix; Bibliography; Index.

### An Introduction to Numerical Methods

Previous editions of this popular textbook offered an accessible and practical introduction to numerical analysis. An Introduction to Numerical Methods: A MATLAB® Approach, Fourth Edition continues to present a wide range of useful and important algorithms for scientific and engineering applications. The authors use MATLAB to illustrate each numerical method, providing full details of the computed results so that the main steps are easily visualized and interpreted. This edition also includes a new chapter on Dynamical Systems and Chaos.

### Introduction to Numerical Analysis

On the occasion of this new edition, the text was enlarged by several new sections. Two sections on B-splines and their computation were added to the chapter on spline functions: Due to their special properties, their flexibility, and the availability of well-tested programs for their computation, B-splines play an important role in many applications. Also, the authors followed suggestions by many readers to supplement the chapter on elimination methods with a section dealing with the solution of large sparse systems of linear equations. Even though such systems are usually solved by iterative methods, the realm of elimination methods has been widely extended due to powerful techniques for handling sparse matrices. We will explain some of these techniques in connection with the Cholesky algorithm for solving positive definite linear systems. The chapter on eigenvalue problems was enlarged by a section on the Lanczos algorithm; the sections on the LR and QR algorithm were rewritten and now contain a description of implicit shift techniques. In order to some extent take into account the progress in the area of ordinary differential equations, a new section on implicit differential equa tions and differential-algebraic systems was added, and the section on stiff differential equations was updated by describing further methods to solve such equations.

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Publisher: Oxford University Press on Demand

ISBN: 9780198506935

Category: Computers

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