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| elementary numerical methods: Elementary Numerical Analysis Kendall E. Atkinson, Weimin Han, 2004 Offering a clear, precise, and accessible presentation, complete with MATLAB programs, this new Third Edition of Elementary Numerical Analysis gives students the support they need to master basic numerical analysis and scientific computing. Now updated and revised, this significant revision features reorganized and rewritten content, as well as some new additional examples and problems.The text introduces core areas of numerical analysis and scientific computing along with basic themes of numerical analysis such as the approximation of problems by simpler methods, the construction of algorithms, iteration methods, error analysis, stability, asymptotic error formulas, and the effects of machine arithmetic. |
| elementary numerical methods: Elementary Numerical Methods Ronald Ernest SCRATON, 1965 |
| elementary numerical methods: Elementary Numerical Analysis S. D. Conte, Carl De Boor, 2018-02-27 This book provides a thorough and careful introduction to the theory and practice of scientific computing at an elementary, yet rigorous, level, from theory via examples and algorithms to computer programs. The original FORTRAN programs have been rewritten in MATLAB and now appear in a new appendix and online, offering a modernized version of this classic reference for basic numerical algorithms. |
| elementary numerical methods: Elementary Numerical Computing with Mathematica Robert D. Skeel, Jerry B. Keiper, 1993 Mathematics of Computing -- Numerical Analysis. |
| elementary numerical methods: Elementary Numerical Methods R. E. Scraton, 1965 |
| elementary numerical methods: Numerical Methods in Engineering with Python 3 Jaan Kiusalaas, 2013-01-21 Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language. |
| elementary numerical methods: Elementary Theory & Application of Numerical Analysis James Edward Miller, David G. Moursund, Charles S. Duris, 2011-01-01 This updated introduction to modern numerical analysis is a complete revision of a classic text originally written in Fortran but now featuring the programming language C++. It focuses on a relatively small number of basic concepts and techniques. Many exercises appear throughout the text, most with solutions. An extensive tutorial explains how to solve problems with C++. |
| elementary numerical methods: Numerical Methods in Scientific Computing: Germund Dahlquist, Ake Bjorck, 2008-09-04 This work addresses the increasingly important role of numerical methods in science and engineering. It combines traditional and well-developed topics with other material such as interval arithmetic, elementary functions, operator series, convergence acceleration, and continued fractions. |
| elementary numerical methods: Elementary Numerical Methods M. J. Jamieson, 1983 |
| elementary numerical methods: An Introduction to Numerical Analysis Kendall Atkinson, 1991-01-16 This Second Edition of a standard numerical analysis text retains organization of the original edition, but all sections have been revised, some extensively, and bibliographies have been updated. New topics covered include optimization, trigonometric interpolation and the fast Fourier transform, numerical differentiation, the method of lines, boundary value problems, the conjugate gradient method, and the least squares solutions of systems of linear equations. Contains many problems, some with solutions. |
| elementary numerical methods: Numerical Methods for Solving Partial Differential Equations George F. Pinder, 2018-02-05 A comprehensive guide to numerical methods for simulating physical-chemical systems This book offers a systematic, highly accessible presentation of numerical methods used to simulate the behavior of physical-chemical systems. Unlike most books on the subject, it focuses on methodology rather than specific applications. Written for students and professionals across an array of scientific and engineering disciplines and with varying levels of experience with applied mathematics, it provides comprehensive descriptions of numerical methods without requiring an advanced mathematical background. Based on its author’s more than forty years of experience teaching numerical methods to engineering students, Numerical Methods for Solving Partial Differential Equations presents the fundamentals of all of the commonly used numerical methods for solving differential equations at a level appropriate for advanced undergraduates and first-year graduate students in science and engineering. Throughout, elementary examples show how numerical methods are used to solve generic versions of equations that arise in many scientific and engineering disciplines. In writing it, the author took pains to ensure that no assumptions were made about the background discipline of the reader. Covers the spectrum of numerical methods that are used to simulate the behavior of physical-chemical systems that occur in science and engineering Written by a professor of engineering with more than forty years of experience teaching numerical methods to engineers Requires only elementary knowledge of differential equations and matrix algebra to master the material Designed to teach students to understand, appreciate and apply the basic mathematics and equations on which Mathcad and similar commercial software packages are based Comprehensive yet accessible to readers with limited mathematical knowledge, Numerical Methods for Solving Partial Differential Equations is an excellent text for advanced undergraduates and first-year graduate students in the sciences and engineering. It is also a valuable working reference for professionals in engineering, physics, chemistry, computer science, and applied mathematics. |
| elementary numerical methods: Numerical Methods in Structural Mechanics Zdenek Bittnar, Jiri Sejnoha, 1996-04-05 A detailed presentation is offered of the fundamental equations in solid mechanics focusing on constitutive equations including quasibrittle materials. Details are provided on individual numerical algorithms, with a heavier emphasis placed on the understanding of basic principles. |
| elementary numerical methods: Elementary Numerical Mathematics for Programmers and Engineers Gisbert Stoyan, Agnes Baran, 2016-11-09 This book covers the basics of numerical methods, while avoiding the definition-theorem-proof style and instead focusing on numerical examples and simple pseudo-codes. The book is divided into ten chapters. Starting with floating number calculations and continuing up to ordinary differential equations, including Euler backwards. The final chapter discusses practical error estimations. Exercises (including several in MATLAB) are provided at the end of each chapter. Suitable for readers with minimal mathematical knowledge, the book not only offers an elementary introduction to numerical mathematics for programmers and engineers but also provides supporting material for students and teachers of mathematics. |
| elementary numerical methods: Numerical Methods for Evolutionary Differential Equations Uri M. Ascher, 2008-09-04 Develops, analyses, and applies numerical methods for evolutionary, or time-dependent, differential problems. |
| elementary numerical methods: Elementary Numerical Analysis Samuel Daniel Conte, Carl De Boor, 1972 |
| elementary numerical methods: Precise Numerical Methods Using C++ Oliver Aberth, 1998 This book explains how precise numerical analysis is constructed with C++. Included is a CD-ROM which contains executable Windows 95 programs for the PC and which demonstrates how these programs can be used to solvetypical problems of elementary numerical analysis with precision. The book also provides exercises which illustrate points from the text and references for the methods presented. |
| elementary numerical methods: Elementary Numerical Analysis Kendall Atkinson, 1985-02-12 A concise introduction to numerical analysis for students in the sciences, mathematics, and engineering. In addition to coverage of all standard topics, it explores approximation methods, construction of algorithms, iteration methods, error analysis, stability, asymptotic error formulas, and the effects of machine arithmetic. Computer programming applications are given in Fortran 77. Features numerous problems and exercises at the end of each section. |
| elementary numerical methods: Numerical Algorithms Justin Solomon, 2015-06-24 Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics presents a new approach to numerical analysis for modern computer scientists. Using examples from a broad base of computational tasks, including data processing, computational photography, and animation, the textbook introduces numerical modeling and algorithmic desig |
| elementary numerical methods: Numerical Methods for Engineers Santosh K Gupta, 1995 This Book Is Intended To Be A Text For Either A First Or A Second Course In Numerical Methods For Students In All Engineering Disciplines. Difficult Concepts, Which Usually Pose Problems To Students Are Explained In Detail And Illustrated With Solved Examples. Enough Elementary Material That Could Be Covered In The First-Level Course Is Included, For Example, Methods For Solving Linear And Nonlinear Algebraic Equations, Interpolation, Differentiation, Integration, And Simple Techniques For Integrating Odes And Pdes (Ordinary And Partial Differential Equations).Advanced Techniques And Concepts That Could Form Part Of A Second-Level Course Includegears Method For Solving Ode-Ivps (Initial Value Problems), Stiffness Of Ode- Ivps, Multiplicity Of Solutions, Convergence Characteristics, The Orthogonal Collocation Method For Solving Ode-Bvps (Boundary Value Problems) And Finite Element Techniques. An Extensive Set Of Graded Problems, Often With Hints, Has Been Included.Some Involve Simple Applications Of The Concepts And Can Be Solved Using A Calculator, While Several Are From Real-Life Situations And Require Writing Computer Programs Or Use Of Library Subroutines. Practice On These Is Expected To Build Up The Reader'S Confidence In Developing Large Computer Codes. |
| elementary numerical methods: Numerical Methods for Two-point Boundary-value Problems Herbert Bishop Keller, 1992 A brief, elementary yet rigorous account of practical numerical methods for solving very general two-point boundary-value problems. Advanced undergraduate level. Over 100 problems. |
| elementary numerical methods: Numerical Methods in Economics Kenneth L. Judd, 2023-04-04 To harness the full power of computer technology, economists need to use a broad range of mathematical techniques. In this book, Kenneth Judd presents techniques from the numerical analysis and applied mathematics literatures and shows how to use them in economic analyses. The book is divided into five parts. Part I provides a general introduction. Part II presents basics from numerical analysis on R^n, including linear equations, iterative methods, optimization, nonlinear equations, approximation methods, numerical integration and differentiation, and Monte Carlo methods. Part III covers methods for dynamic problems, including finite difference methods, projection methods, and numerical dynamic programming. Part IV covers perturbation and asymptotic solution methods. Finally, Part V covers applications to dynamic equilibrium analysis, including solution methods for perfect foresight models and rational expectation models. A website contains supplementary material including programs and answers to exercises. |
| elementary numerical methods: Numerical Methods for Engineers Steven C. Chapra, Raymond P. Canale, 2006 The fifth edition of Numerical Methods for Engineers continues its tradition of excellence. Instructors love this text because it is a comprehensive text that is easy to teach from. Students love it because it is written for them--with great pedagogy and clear explanations and examples throughout. The text features a broad array of applications, including all engineering disciplines. The revision retains the successful pedagogy of the prior editions. Chapra and Canale's unique approach opens each part of the text with sections called Motivation, Mathematical Background, and Orientation, preparing the student for what is to come in a motivating and engaging manner. Each part closes with an Epilogue containing sections called Trade-Offs, Important Relationships and Formulas, and Advanced Methods and Additional References. Much more than a summary, the Epilogue deepens understanding of what has been learned and provides a peek into more advanced methods. Users will find use of software packages, specifically MATLAB and Excel with VBA. This includes material on developing MATLAB m-files and VBA macros. Approximately 80% of the problems are new or revised for this edition. The expanded breadth of engineering disciplines covered is especially evident in the problems, which now cover such areas as biotechnology and biomedical engineering. |
| elementary numerical methods: Box Splines Carl de Boor, Klaus Höllig, Sherman Riemenschneider, 2013-03-09 Compactly supported smooth piecewise polynomial functions provide an efficient tool for the approximation of curves and surfaces and other smooth functions of one and several arguments. Since they are locally polynomial, they are easy to evaluate. Since they are smooth, they can be used when smoothness is required, as in the numerical solution of partial differential equations (in the Finite Element method) or the modeling of smooth sur faces (in Computer Aided Geometric Design). Since they are compactly supported, their linear span has the needed flexibility to approximate at all, and the systems to be solved in the construction of approximations are 'banded'. The construction of compactly supported smooth piecewise polynomials becomes ever more difficult as the dimension, s, of their domain G ~ IRs, i. e. , the number of arguments, increases. In the univariate case, there is only one kind of cell in any useful partition, namely, an interval, and its boundary consists of two separated points, across which polynomial pieces would have to be matched as one constructs a smooth piecewise polynomial function. This can be done easily, with the only limitation that the num ber of smoothness conditions across such a breakpoint should not exceed the polynomial degree (since that would force the two joining polynomial pieces to coincide). In particular, on any partition, there are (nontrivial) compactly supported piecewise polynomials of degree ~ k and in C(k-l), of which the univariate B-spline is the most useful example. |
| elementary numerical methods: Numerical Methods of Reactor Analysis Melville Jr. Clark, 2012-12-02 Nuclear Science and Technology, Volume 3: Numerical Methods of Reactor Analysis presents the numerical analysis frequently used in the nuclear reactor field. This book discusses the numerical approximation for the multigroup diffusion method, which results in simple algebraic equations. Organized into six chapters, this volume starts with an overview of the simplified formulation of linear algebra by defining the matrices and operations with matrices. This text then discusses the properties of special matrices and reviews the elementary properties of finite difference equations. Other chapters consider a variety of methods of obtaining numerical solutions to the approximating equations. The final chapter deals with Monte Carlo method, which is a statistical method for solving statistical or deterministic problems. This book is a valuable resource for nuclear engineers. Students at the graduate level who had an introductory course in reactor physics and a basic course in differential equations will also find this book useful. |
| elementary numerical methods: Partial Differential Equations with Numerical Methods Stig Larsson, Vidar Thomee, 2008-12-05 The main theme is the integration of the theory of linear PDE and the theory of finite difference and finite element methods. For each type of PDE, elliptic, parabolic, and hyperbolic, the text contains one chapter on the mathematical theory of the differential equation, followed by one chapter on finite difference methods and one on finite element methods. The chapters on elliptic equations are preceded by a chapter on the two-point boundary value problem for ordinary differential equations. Similarly, the chapters on time-dependent problems are preceded by a chapter on the initial-value problem for ordinary differential equations. There is also one chapter on the elliptic eigenvalue problem and eigenfunction expansion. The presentation does not presume a deep knowledge of mathematical and functional analysis. The required background on linear functional analysis and Sobolev spaces is reviewed in an appendix. The book is suitable for advanced undergraduate and beginning graduate students of applied mathematics and engineering. |
| elementary numerical methods: Elementary Numerical Analysis Samuel Daniel Conte, Carl De Boor, 1983 |
| elementary numerical methods: Elementary Numerical Analysis Charles Brown Tompkins, Walter L. Wilson (Jr.), 1969 |
| elementary numerical methods: Numerical Analysis for Statisticians Kenneth Lange, 2010-05-17 Numerical analysis is the study of computation and its accuracy, stability and often its implementation on a computer. This book focuses on the principles of numerical analysis and is intended to equip those readers who use statistics to craft their own software and to understand the advantages and disadvantages of different numerical methods. |
| elementary numerical methods: Elementary Mechanics Using Matlab Anders Malthe-Sørenssen, 2016-10-17 This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks. Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts. While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Matlab, and a chapter devoted to the basics of scientific programming with Matlab is included. A parallel edition using Python instead of Matlab is also available. Last but not least, each chapter is accompanied by an extensive set of course-tested exercises and solutions. |
| elementary numerical methods: An Introduction to Programming and Numerical Methods in MATLAB Steve Otto, James P. Denier, 2005-12-06 An elementary first course for students in mathematics and engineering Practical in approach: examples of code are provided for students to debug, and tasks – with full solutions – are provided at the end of each chapter Includes a glossary of useful terms, with each term supported by an example of the syntaxes commonly encountered |
| elementary numerical methods: Numerical Methods for Large Eigenvalue Problems Yousef Saad, 2011-05-26 This revised edition discusses numerical methods for computing the eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications. Each chapter was updated by shortening or deleting outdated topics, adding topics of more recent interest and adapting the Notes and References section. Significant changes have been made to Chapters 6 through 8, which describe algorithms and their implementations and now include topics such as the implicit restart techniques, the Jacobi-Davidson method and automatic multilevel substructuring. |
| elementary numerical methods: Numerical Methods of Exploration Seismology Gary F. Margrave, Michael P. Lamoureux, 2019-01-10 Technical guide to the theory and practice of seismic data processing with MATLAB algorithms for advanced students, researchers and professionals. |
| elementary numerical methods: Numerical Methods that Work Forman S. Acton, 2020-07-31 |
| elementary numerical methods: Numerical Computational Methods Prabhakar Baliram Patil, U. P. Verma, 2009 Though Analytical and/or Experimental solutions for every problem are not possible, approximate solutions are. Numerical methods provide the best approximation among all. Numerical Computational Methods presents a host of numerical methods, their algorithmic presentation and computer programs in Visual Basic, FORTRAN and C++. Perhaps it is for the first time that any book provides numerical methods in Visual Basic. The text is exhaustive and illuminates basic derivations of the formulae to be converted into programs. For each program algorithm is expressed and each step of the algorithm can be directly converted into computer program statement. All topics in the book are explicit in nature, self explanatory and student friendly. Solved problems accelerate the grasp of the particular numerical method. This book can be used both as a text and a good reference book for any researcher who needs numerical evaluations his work. The reader is expected to have only elementary knowledge of differentiation and integration. |
| elementary numerical methods: Elementary Analysis Kenneth A. Ross, 2013-04-17 Designed for students having no previous experience with rigorous proofs, this text on analysis can be used immediately following standard calculus courses. It is highly recommended for anyone planning to study advanced analysis, e.g., complex variables, differential equations, Fourier analysis, numerical analysis, several variable calculus, and statistics. It is also recommended for future secondary school teachers. A limited number of concepts involving the real line and functions on the real line are studied. Many abstract ideas, such as metric spaces and ordered systems, are avoided. The least upper bound property is taken as an axiom and the order properties of the real line are exploited throughout. A thorough treatment of sequences of numbers is used as a basis for studying standard calculus topics. Optional sections invite students to study such topics as metric spaces and Riemann-Stieltjes integrals. |
| elementary numerical methods: Elementary Numerical Methods James Henry Mayhew, 1967 |
| elementary numerical methods: COMPUTER ORIENTED NUMERICAL METHODS RAJARAMAN, V., 2018-11-01 This book is a concise and lucid introduction to computer oriented numerical methods with well-chosen graphical illustrations that give an insight into the mechanism of various methods. The book develops computational algorithms for solving non-linear algebraic equation, sets of linear equations, curve-fitting, integration, differentiation, and solving ordinary differential equations. OUTSTANDING FEATURES • Elementary presentation of numerical methods using computers for solving a variety of problems for students who have only basic level knowledge of mathematics. • Geometrical illustrations used to explain how numerical algorithms are evolved. • Emphasis on implementation of numerical algorithm on computers. • Detailed discussion of IEEE standard for representing floating point numbers. • Algorithms derived and presented using a simple English based structured language. • Truncation and rounding errors in numerical calculations explained. • Each chapter starts with learning goals and all methods illustrated with numerical examples. • Appendix gives pointers to open source libraries for numerical computation. |
| elementary numerical methods: Numerical Analysis Rainer Kress, 2012-12-06 No applied mathematician can be properly trained without some basic un derstanding ofnumerical methods, Le., numerical analysis. And no scientist and engineer should be using a package program for numerical computa tions without understanding the program's purpose and its limitations. This book is an attempt to provide some of the required knowledge and understanding. It is written in a spirit that considers numerical analysis not merely as a tool for solving applied problems but also as a challenging and rewarding part of mathematics. The main goal is to provide insight into numerical analysis rather than merely to provide numerical recipes. The book evolved from the courses on numerical analysis I have taught since 1971 at the University ofGottingen and may be viewed as a successor of an earlier version jointly written with Bruno Brosowski [10] in 1974. It aims at presenting the basic ideas of numerical analysis in a style as concise as possible. Its volume is scaled to a one-yearcourse, i.e., a two-semester course, addressing second-yearstudents at a German university or advanced undergraduate or first-year graduate students at an American university. |
| elementary numerical methods: Numerical Methods, Software, and Analysis John Rischard Rice, 1983 Mathematics and computer science background. Numerical software. Errors, roud-off, and stabilitly. Models and formulas for numerical computations. Interpolation. Matrices and linear equations. Differentiation and integration. Nonlinear equations. Ordinary differential equations. Partial differential equations. Approximation of functions and data. Software practice, costs, and engineering. Software performance evaluation. The validation of numerical computations. Protran. |
| elementary numerical methods: Numerical Analysis Timothy Sauer, 2013-07-26 Numerical Analysis, Second Edition, is a modern and readable text for the undergraduate audience. This book covers not only the standard topics but also some more advanced numerical methods being used by computational scientists and engineers-topics such as compression, forward and backward error analysis, and iterative methods of solving equations-all while maintaining a level of discussion appropriate for undergraduates. Each chapter contains a Reality Check, which is an extended exploration of relevant application areas that can launch individual or team projects. MATLAB(r) is used throughout to demonstrate and implement numerical methods. The Second Edition features many noteworthy improvements based on feedback from users, such as new coverage of Cholesky factorization, GMRES methods, and nonlinear PDEs. |
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