Author: John H. Mathews
Publisher: Prentice Hall
ISBN:
Category : Mathematics
Languages : en
Pages : 536

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Book Description

Author: Joe D. Hoffman
Publisher: CRC Press
ISBN: 1482270609
Category : Mathematics
Languages : en
Pages : 840

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Book Description
Emphasizing the finite difference approach for solving differential equations, the second edition of Numerical Methods for Engineers and Scientists presents a methodology for systematically constructing individual computer programs. Providing easy access to accurate solutions to complex scientific and engineering problems, each chapter begins with objectives, a discussion of a representative application, and an outline of special features, summing up with a list of tasks students should be able to complete after reading the chapter- perfect for use as a study guide or for review. The AIAA Journal calls the book "...a good, solid instructional text on the basic tools of numerical analysis."

Author: John H. Mathews
Publisher:
ISBN: 9780136250470
Category : Numerical analysis
Languages : en
Pages : 646

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Book Description
A modern, computer-oriented approach to numerical analysis that shows how the mathematics of calculus and linear algebra are implemented in computer algorithms. Computer output is displayed in tables and used to develop topics of computer accuracy, pitfalls in computational methods and error estimation.

Author: Robert W. Hornbeck
Publisher: Prentice Hall
ISBN:
Category : Computers
Languages : en
Pages : 326

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Book Description
Using a "learn by example" approach, this exploration of the fundamental tools of numerical methods covers both modern and older, well-established techniques that are well-suited to the digital-computer solution of problems in many areas of science and engineering.

Author: Anne Greenbaum
Publisher: Princeton University Press
ISBN: 1400842670
Category : Mathematics
Languages : en
Pages : 471

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Book Description
A rigorous and comprehensive introduction to numerical analysis Numerical Methods provides a clear and concise exploration of standard numerical analysis topics, as well as nontraditional ones, including mathematical modeling, Monte Carlo methods, Markov chains, and fractals. Filled with appealing examples that will motivate students, the textbook considers modern application areas, such as information retrieval and animation, and classical topics from physics and engineering. Exercises use MATLAB and promote understanding of computational results. The book gives instructors the flexibility to emphasize different aspects—design, analysis, or computer implementation—of numerical algorithms, depending on the background and interests of students. Designed for upper-division undergraduates in mathematics or computer science classes, the textbook assumes that students have prior knowledge of linear algebra and calculus, although these topics are reviewed in the text. Short discussions of the history of numerical methods are interspersed throughout the chapters. The book also includes polynomial interpolation at Chebyshev points, use of the MATLAB package Chebfun, and a section on the fast Fourier transform. Supplementary materials are available online. Clear and concise exposition of standard numerical analysis topics Explores nontraditional topics, such as mathematical modeling and Monte Carlo methods Covers modern applications, including information retrieval and animation, and classical applications from physics and engineering Promotes understanding of computational results through MATLAB exercises Provides flexibility so instructors can emphasize mathematical or applied/computational aspects of numerical methods or a combination Includes recent results on polynomial interpolation at Chebyshev points and use of the MATLAB package Chebfun Short discussions of the history of numerical methods interspersed throughout Supplementary materials available online

Author: Richard Wesley Hamming
Publisher:
ISBN:
Category : Electronic digital computers
Languages : en
Pages : 440

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Book Description

Author: Uri M. Ascher
Publisher: SIAM
ISBN: 0898719976
Category : Mathematics
Languages : en
Pages : 574

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Book Description
Offers students a practical knowledge of modern techniques in scientific computing.

Author: Jaan Kiusalaas
Publisher: Cambridge University Press
ISBN: 1107033853
Category : Computers
Languages : en
Pages : 437

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

Author: Norbert Schorghofer
Publisher: CRC Press
ISBN: 1351609815
Category : Science
Languages : en
Pages : 190

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Book Description
Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods, computer technology, and their interconnections, which are treated with the goal of facilitating scientific research across all disciplines. Each chapter provides an insightful lesson and viewpoints from several subject areas are often compounded within a single chapter. Written with an eye on usefulness, longevity, and breadth, Lessons in Scientific Computing will serve as a "one stop shop" for students taking a unified course in scientific computing, or seeking a single cohesive text spanning multiple courses. Features: Provides a unique combination of numerical analysis, computer programming, and computer hardware in a single text Includes essential topics such as numerical methods, approximation theory, parallel computing, algorithms, and examples of computational discoveries in science Written in a clear and engaging style Not wedded to a specific programming language

Author: Johan Hoffman
Publisher: SIAM
ISBN: 1611976723
Category : Computers
Languages : en
Pages : 425

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Book Description
Computational methods are an integral part of most scientific disciplines, and a rudimentary understanding of their potential and limitations is essential for any scientist or engineer. This textbook introduces computational science through a set of methods and algorithms, with the aim of familiarizing the reader with the field’s theoretical foundations and providing the practical skills to use and develop computational methods. Centered around a set of fundamental algorithms presented in the form of pseudocode, this self-contained textbook extends the classical syllabus with new material, including high performance computing, adjoint methods, machine learning, randomized algorithms, and quantum computing. It presents theoretical material alongside several examples and exercises and provides Python implementations of many key algorithms. Methods in Computational Science is for advanced undergraduate and graduate-level students studying computer science and data science. It can also be used to support continuous learning for practicing mathematicians, data scientists, computer scientists, and engineers in the field of computational science. It is appropriate for courses in advanced numerical analysis, data science, numerical optimization, and approximation theory.