Download or read book Practical Scientific Computing written by Muhammad Ali and published by Elsevier. This book was released on 2011-02-26 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific computing is about developing mathematical models, numerical methods and computer implementations to study and solve real problems in science, engineering, business and even social sciences. Mathematical modelling requires deep understanding of classical numerical methods. This essential guide provides the reader with sufficient foundations in these areas to venture into more advanced texts.The first section of the book presents numEclipse, an open source tool for numerical computing based on the notion of MATLAB®. numEclipse is implemented as a plug-in for Eclipse, a leading integrated development environment for Java programming. The second section studies the classical methods of numerical analysis. Numerical algorithms and their implementations are presented using numEclipse.Practical scientific computing is an invaluable reference for undergraduate engineering, science and mathematics students taking numerical methods courses. It will also be a useful handbook for postgraduate researchers and professionals whose work involves scientific computing. - An invaluable reference for undergraduate engineering, science and mathematics students taking numerical methods courses - Guides the reader through developing a deep understanding of classical numerical methods - Features a comprehensive analysis of numEclipse including numerical algorithms and their implementations

Download or read book Practical Numerical and Scientific Computing with MATLAB and Python written by Eihab B. M. Bashier and published by CRC Press. This book was released on 2020-03-18 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical Numerical and Scientific Computing with MATLAB® and Python 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. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python.

Download or read book Scientific Computing with Case Studies written by Dianne P. O'Leary and published by SIAM. This book was released on 2009-03-19 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.

Download or read book Practical Numerical Computing Using Python written by Mahendra Verma and published by Independently Published. This book was released on 2021-11-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Review: "This excellent book of Prof. Verma is a single resource which a student can use to learn the fast-developing field of computational science. In addition to the description of Python language, it provides a broad overview of hardware, software, classic numerical methods, and everything in between. I recommend it strongly to all!" -- Prof. Prateek Sharma, IISc Bengaluru Key Features of the Book: Perfect book for introduction to practical numerical algorithms and programs for advanced undergraduate and beginning graduate students. Introduces Python programming language and its modules related to numerical computing Covers Numpy, Matplotlib, and Scipy modules in details. Illustrates how to make a variety of plots and animations. Detailed discussions on important numerical algorithms: Interpolation, Integration, Differentiation, ODE and PDE solvers, and Linear algebra solvers. Practical implementation of the algorithms in Python. Introduces Spectral and Finite-difference methods and applications to fluid mechanics and quantum mechanics. Includes chapters on Monte Carlo methods and applications to statistical physics, as well as on error analysis. A brief introduction to Computer hardware, complexity estimates, and nondimensionalization.

Download or read book Advanced Scientific Computing in BASIC with Applications in Chemistry Biology and Pharmacology written by P Valko and published by Elsevier. This book was released on 1989-01-01 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a practical introduction to numerical methods and presents BASIC subroutines for real-life computations in the areas of chemistry, biology, and pharmacology. The choice of BASIC as the programming language is motivated by its simplicity, its availability on all personal computers and by its power in data acquisition. While most of the scientific packages currently available in BASIC date back to the period of limited memory and speed, the subroutines presented here can handle a broad range of realistic problems with the power and sophistication needed by professionals and with simple, step-by-step instructions for students and beginners.Please note that a diskette containing the 37 program modules and 39 sample programs listed in the book is no longer available.The main task considered in the book is that of extracting useful information from measurements via modelling, simulation, and statistical data evaluations. Efficient and robust numerical methods have been chosen to solve related problems in numerical algebra, nonlinear equations and optimization, parameter estimation, signal processing, and differential equations. For each class of routines an introduction to the relevant theory and techniques is given, so that the reader will recognise and use the appropriate method for solving his or her particular problem. Simple examples illustrate the use and applicability of each method.

Download or read book Applied Scientific Computing written by Peter R. Turner and published by Springer. This book was released on 2018-07-18 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python. Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge–Kutta, and shooting methods; presents largely self-contained chapters, arranged in a logical order suitable for an introductory course on scientific computing. Undergraduate students embarking on a first course on numerical methods or scientific computing will find this textbook to be an invaluable guide to the field, and to the application of these methods across such varied disciplines as computer science, engineering, mathematics, economics, the physical sciences, and social science.

Download or read book Mathematical Principles for Scientific Computing and Visualization written by Gerald Farin and published by CRC Press. This book was released on 2008-10-21 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This non-traditional introduction to the mathematics of scientific computation describes the principles behind the major methods, from statistics, applied mathematics, scientific visualization, and elsewhere, in a way that is accessible to a large part of the scientific community. Introductory material includes computational basics, a review of coo

Download or read book Guide to Scientific Computing in C written by Joe Pitt-Francis and published by Springer Science & Business Media. This book was released on 2012-02-15 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-read textbook/reference presents an essential guide to object-oriented C++ programming for scientific computing. With a practical focus on learning by example, the theory is supported by numerous exercises. Features: provides a specific focus on the application of C++ to scientific computing, including parallel computing using MPI; stresses the importance of a clear programming style to minimize the introduction of errors into code; presents a practical introduction to procedural programming in C++, covering variables, flow of control, input and output, pointers, functions, and reference variables; exhibits the efficacy of classes, highlighting the main features of object-orientation; examines more advanced C++ features, such as templates and exceptions; supplies useful tips and examples throughout the text, together with chapter-ending exercises, and code available to download from Springer.

Download or read book An Introduction to High performance Scientific Computing written by Lloyd Dudley Fosdick and published by MIT Press. This book was released on 1996 with total page 838 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. This text evolved from a new curriculum in scientific computing that was developed to teach undergraduate science and engineering majors how to use high-performance computing systems (supercomputers) in scientific and engineering applications. Designed for undergraduates, An Introduction to High-Performance Scientific Computing assumes a basic knowledge of numerical computation and proficiency in Fortran or C programming and can be used in any science, computer science, applied mathematics, or engineering department or by practicing scientists and engineers, especially those associated with one of the national laboratories or supercomputer centers. The authors begin with a survey of scientific computing and then provide a review of background (numerical analysis, IEEE arithmetic, Unix, Fortran) and tools (elements of MATLAB, IDL, AVS). Next, full coverage is given to scientific visualization and to the architectures (scientific workstations and vector and parallel supercomputers) and performance evaluation needed to solve large-scale problems. The concluding section on applications includes three problems (molecular dynamics, advection, and computerized tomography) that illustrate the challenge of solving problems on a variety of computer architectures as well as the suitability of a particular architecture to solving a particular problem. Finally, since this can only be a hands-on course with extensive programming and experimentation with a variety of architectures and programming paradigms, the authors have provided a laboratory manual and supporting software via anonymous ftp. Scientific and Engineering Computation series

Download or read book Lessons in Scientific Computing written by Norbert Schorghofer and published by CRC Press. This book was released on 2018-09-25 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Not wedded to a specific programming language

Download or read book Elements of Scientific Computing written by Aslak Tveito and published by Springer Science & Business Media. This book was released on 2010-09-24 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: Science used to be experiments and theory, now it is experiments, theory and computations. The computational approach to understanding nature and technology is currently flowering in many fields such as physics, geophysics, astrophysics, chemistry, biology, and most engineering disciplines. This book is a gentle introduction to such computational methods where the techniques are explained through examples. It is our goal to teach principles and ideas that carry over from field to field. You will learn basic methods and how to implement them. In order to gain the most from this text, you will need prior knowledge of calculus, basic linear algebra and elementary programming.

Download or read book A First Course in Scientific Computing written by Rubin Landau and published by Princeton University Press. This book was released on 2011-10-30 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a new approach to introductory scientific computing. It aims to make students comfortable using computers to do science, to provide them with the computational tools and knowledge they need throughout their college careers and into their professional careers, and to show how all the pieces can work together. Rubin Landau introduces the requisite mathematics and computer science in the course of realistic problems, from energy use to the building of skyscrapers to projectile motion with drag. He is attentive to how each discipline uses its own language to describe the same concepts and how computations are concrete instances of the abstract. Landau covers the basics of computation, numerical analysis, and programming from a computational science perspective. The first part of the printed book uses the problem-solving environment Maple as its context, with the same material covered on the accompanying CD as both Maple and Mathematica programs; the second part uses the compiled language Java, with equivalent materials in Fortran90 on the CD; and the final part presents an introduction to LaTeX replete with sample files. Providing the essentials of computing, with practical examples, A First Course in Scientific Computing adheres to the principle that science and engineering students learn computation best while sitting in front of a computer, book in hand, in trial-and-error mode. Not only is it an invaluable learning text and an essential reference for students of mathematics, engineering, physics, and other sciences, but it is also a consummate model for future textbooks in computational science and engineering courses. A broad spectrum of computing tools and examples that can be used throughout an academic career Practical computing aimed at solving realistic problems Both symbolic and numerical computations A multidisciplinary approach: science + math + computer science Maple and Java in the book itself; Mathematica, Fortran90, Maple and Java on the accompanying CD in an interactive workbook format

Download or read book Scientific Programming and Computer Architecture written by Divakar Viswanath and published by MIT Press. This book was released on 2017-07-28 with total page 625 pages. Available in PDF, EPUB and Kindle. Book excerpt: A variety of programming models relevant to scientists explained, with an emphasis on how programming constructs map to parts of the computer. What makes computer programs fast or slow? To answer this question, we have to get behind the abstractions of programming languages and look at how a computer really works. This book examines and explains a variety of scientific programming models (programming models relevant to scientists) with an emphasis on how programming constructs map to different parts of the computer's architecture. Two themes emerge: program speed and program modularity. Throughout this book, the premise is to "get under the hood," and the discussion is tied to specific programs. The book digs into linkers, compilers, operating systems, and computer architecture to understand how the different parts of the computer interact with programs. It begins with a review of C/C++ and explanations of how libraries, linkers, and Makefiles work. Programming models covered include Pthreads, OpenMP, MPI, TCP/IP, and CUDA.The emphasis on how computers work leads the reader into computer architecture and occasionally into the operating system kernel. The operating system studied is Linux, the preferred platform for scientific computing. Linux is also open source, which allows users to peer into its inner workings. A brief appendix provides a useful table of machines used to time programs. The book's website (https://github.com/divakarvi/bk-spca) has all the programs described in the book as well as a link to the html text.

Download or read book Introduction to Scientific Computing and Data Analysis written by Mark H. Holmes and published by Springer Nature. This book was released on 2023-07-11 with total page 563 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.

Download or read book Learning SciPy for Numerical and Scientific Computing Second Edition written by Sergio J. Rojas G. and published by Packt Publishing Ltd. This book was released on 2015-02-26 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book targets programmers and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.

Download or read book Scientific Computing with Case Studies written by Dianne P. O'Leary and published by SIAM. This book was released on 2009-01-01 with total page 377 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the numerical solution of linear and nonlinear equations, differential equations, optimization problems, and eigenvalue problems. It treats standard problems and introduces important variants such as sparse systems, differential-algebraic equations, constrained optimization, Monte Carlo simulations, and parametric studies. Stability and error analysis are emphasized, and the Matlab algorithms are grounded in sound principles of software design and understanding of machine arithmetic and memory management. Nineteen case studies provide experience in mathematical modeling and algorithm design, motivated by problems in physics, engineering, epidemiology, chemistry, and biology. The topics included go well beyond the standard first-course syllabus, introducing important problems such as differential-algebraic equations and conic optimization problems, and important solution techniques such as continuation methods. The case studies cover a wide variety of fascinating applications, from modeling the spread of an epidemic to determining truss configurations.

Download or read book Numerical Methods in Scientific Computing written by Germund Dahlquist and published by SIAM. This book was released on 2008-01-01 with total page 742 pages. Available in PDF, EPUB and Kindle. Book excerpt: This new book from the authors of the classic book Numerical methods addresses the increasingly important role of numerical methods in science and engineering. More cohesive and comprehensive than any other modern textbook in the field, it combines traditional and well-developed topics with other material that is rarely found in numerical analysis texts, such as interval arithmetic, elementary functions, operator series, convergence acceleration, and continued fractions. Although this volume is self-contained, more comprehensive treatments of matrix computations will be given in a forthcoming volume. A supplementary Website contains three appendices: an introduction to matrix computations; a description of Mulprec, a MATLAB multiple precision package; and a guide to literature, algorithms, and software in numerical analysis. Review questions, problems, and computer exercises are also included. For use in an introductory graduate course in numerical analysis and for researchers who use numerical methods in science and engineering.