Catalogue


Applied numerical methods using MATLAB [electronic resource] /
Won Young Yang ... [et al.].
imprint
Hoboken, N.J. : Wiley-Interscience, c2005.
description
xiv, 509 p. : ill.
ISBN
0471698334 (cloth)
format(s)
Book
Holdings
Subjects
title subject
More Details
added author
imprint
Hoboken, N.J. : Wiley-Interscience, c2005.
isbn
0471698334 (cloth)
restrictions
Licensed for access by U. of T. users.
catalogue key
7834411
 
Includes bibliographical references (p. 497-498) and indexes.
A Look Inside
Full Text Reviews
Appeared in Choice on 2005-11-01:
Yang (Chung-Ang Univ., Korea) and colleagues focus on some fundamental mathematical concepts in numerical analysis with MATLAB applications, in a well-written and organized format. The first chapter is an introduction to MATLAB, with tips for recognizing and avoiding computational errors. Subsequent chapters discuss linear and nonlinear equations, interpolation and curve fitting, numerical differentiation and integration, matrices and eigenvalues, and optimization with MATLAB built-in routines. The book concludes with ordinary and partial differential equations. Nine appendixes cover the most useful mathematical theorems and properties, including the Fourier and Laplace transforms. The MATLAB functions are well illustrated with several examples. For academic libraries, mathematicians, students, and working professionals. ^BSumming Up: Highly recommended. Upper-division undergraduates through professionals. S. T. Karris formerly, University of California, Berkeley
Reviews
Review Quotes
"For academic libraries, mathematicians, students, and working professionals...highly recommended." ( CHOICE , November 2005)
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Choice, November 2005
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Summaries
Back Cover Copy
Learn how to use MATLAB to solve complex numerical problems Increasingly, scientists and engineers favor MATLAB over conventional programming languages such as FORTRAN and C when they wish to solve complex problems. This book will enable readers to solve problems without needing to understand all the details of the underlying theory of numerical methods. By providing many examples of the uses of similar functions, it guides them towards the selection of the appropriate MATLAB functions for solving their problem efficiently. The authors have incorporated existing MATLAB functions into a series of simplified, yet complete programs that may be readily adapted by students and practitioners to solve real-world engineering and science problems. Key features include: More than 100 supplemental codes Complete MATLAB programs to demonstrate solutions to real-life exercises and problems Downloadable MATLAB programs to correspond with the text Interactive demonstration programs that course instructors can use to produce visual presentations of the solution processes of some algorithms An overview of the Partial Differential Equation (PDE) toolbox An appendix with MATLAB commands/functions for symbolic computation With very little prior programming experience, students and practitioners will find this approach invaluable to quickly learn how to solve their numerical problems.
Back Cover Copy
Learn how to use MATLABr to solve complex numerical problems Increasingly, scientists and engineers favor MATLAB over conventional programming languages such as FORTRAN and C when they wish to solve complex problems. This book will enable readers to solve problems without needing to understand all the details of the underlying theory of numerical methods. By providing many examples of the uses of similar functions, it guides them towards the selection of the appropriate MATLAB functions for solving their problem efficiently. The authors have incorporated existing MATLAB functions into a series of simplified, yet complete programs that may be readily adapted by students and practitioners to solve real-world engineering and science problems. Key features include: More than 100 supplemental codes Complete MATLAB programs to demonstrate solutions to real-life exercises and problems Downloadable MATLAB programs to correspond with the text Interactive demonstration programs that course instructors can use to produce visual presentations of the solution processes of some algorithms An overview of the Partial Differential Equation (PDE) toolbox An appendix with MATLAB commands/functions for symbolic computation With very little prior programming experience, students and practitioners will find this approach invaluable to quickly learn how to solve their numerical problems.
Back Cover Copy
Learn how to use MATLAB? to solve complex numerical problems Increasingly, scientists and engineers favor MATLAB over conventional programming languages such as FORTRAN and C when they wish to solve complex problems. This book will enable readers to solve problems without needing to understand all the details of the underlying theory of numerical methods. By providing many examples of the uses of similar functions, it guides them towards the selection of the appropriate MATLAB functions for solving their problem efficiently. The authors have incorporated existing MATLAB functions into a series of simplified, yet complete programs that may be readily adapted by students and practitioners to solve real-world engineering and science problems. Key features include: More than 100 supplemental codes Complete MATLAB programs to demonstrate solutions to real-life exercises and problems Downloadable MATLAB programs to correspond with the text Interactive demonstration programs that course instructors can use to produce visual presentations of the solution processes of some algorithms An overview of the Partial Differential Equation (PDE) toolbox An appendix with MATLAB commands/functions for symbolic computation With very little prior programming experience, students and practitioners will find this approach invaluable to quickly learn how to solve their numerical problems.
Long Description
Learn how to use MATLABr to solve complex numerical problemsIncreasingly, scientists and engineers favor MATLAB over conventional programming languages such as FORTRAN and C when they wish to solve complex problems. This book will enable readers to solve problems without needing to understand all the details of the underlying theory of numerical methods. By providing many examples of the uses of similar functions, it guides them towards the selection of the appropriate MATLAB functions for solving their problem efficiently.The authors have incorporated existing MATLAB functions into a series of simplified, yet complete programs that may be readily adapted by students and practitioners to solve real-world engineering and science problems. Key features include: More than 100 supplemental codes Complete MATLAB programs to demonstrate solutions to real-life exercises and problems Downloadable MATLAB programs to correspond with the text Interactive demonstration programs that course instructors can use to produce visual presentations of the solution processes of some algorithms An overview of the Partial Differential Equation (PDE) toolbox An appendix with MATLAB commands/functions for symbolic computation With very little prior programming experience, students and practitioners will find this approach invaluable to quickly learn how to solve their numerical problems.
Main Description
In recent years, with the introduction of new media products, there has been a shift in the use of programming languages from FORTRAN or C to MATLAB for implementing numerical methods. This book makes use of the powerful MATLAB software to avoid complex derivations, and to teach the fundamental concepts using the software to solve practical problems. Over the years, many textbooks have been written on the subject of numerical methods. Based on their course experience, the authors use a more practical approach and link every method to real engineering and/or science problems. The main benefit is that engineers don't have to know the mathematical theory in order to apply the numerical methods for solving their real-life problems.
Bowker Data Service Summary
This work makes use of the powerful MATLAB software to avoid complex derivations, and to teach the fundamental concepts using the software to solve practical problems.
Table of Contents
Preface
MATLAB Usage and Computational Errors
Basic Operations of MATLAB
Input/Output of Data from MATLAB Command Window
Input/Output of Data Through Files
Input/Output of Data Using Keyboard
2-D Graphic Input/Output
3-D Graphic Output
Mathematical Functions
Operations on Vectors and Matrices
Random Number Generators
Flow Control
Computer Errors Versus Human Mistakes
IEEE 64-bit Floating-Point Number Representation
Various Kinds of Computing Errors
Absolute/Relative Computing Errors
Error Propagation
Tips for Avoiding Large Errors
Toward Good Program
Nested Computing for Computational Efficiency
Vector Operation Versus Loop Iteration
Iterative Routine Versus Nested Routine
To Avoid Runtime Error
Parameter Sharing via Global Variables
Parameter Passing Through Varargin
Adaptive Input Argument List
Problems
System of Linear Equations
Solution for a System of Linear Equations
The Nonsingular Case (M = N)
The Underdetermined Case (M < N): Minimum-Norm Solution
The Overdetermined Case (M > N): Least-Squares Error Solution
RLSE (Recursive Least-Squares Estimation)
Solving a System of Linear Equations
Gauss Elimination
Partial Pivoting
Gauss-Jordan Elimination
Inverse Matrix
Decomposition (Factorization)
LU Decomposition (Factorization): Triangularization
Other Decomposition (Factorization): Cholesky, QR, and SVD
Iterative Methods to Solve Equations
Jacobi Iteration
Gauss-Seidel Iteration
The Convergence of Jacobi and Gauss-Seidel Iterations
Problems
Interpolation and Curve Fitting
Interpolation by Lagrange Polynomial
Interpolation by Newton Polynomial
Approximation by Chebyshev Polynomial
Pade Approximation by Rational Function
Interpolation by Cubic Spline
Hermite Interpolating Polynomial
Two-dimensional Interpolation
Curve Fitting
Straight Line Fit: A Polynomial Function of First Degree
Polynomial Curve Fit: A Polynomial Function of Higher Degree
Exponential Curve Fit and Other Functions
Fourier Transform
FFT Versus DFT
Physical Meaning of DFT
Interpolation by Using DFS
Problems
Nonlinear Equations
Iterative Method Toward Fixed Point
Bisection Method
False Position or Regula Falsi Method
Newton(-Raphson) Method
Secant Method
Newton Method for a System of Nonlinear Equations
Symbolic Solution for Equations
A Real-World Problem
Problems
Numerical Differentiation/Integration
Difference Approximation for First Derivative
Approximation Error of First Derivative
Difference Approximation for Second and Higher Derivative
Interpolating Polynomial and Numerical Differential
Numerical Integration and Quadrature
Trapezoidal Method and Simpson Method
Recursive Rule and Romberg Integration
Adaptive Quadrature
Gauss Quadrature
Gauss-Legendre Integration
Gauss-Hermite Integration
Gauss-Laguer
Table of Contents provided by Publisher. All Rights Reserved.

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