Applied Numerical Methods with MATLAB 3/e (絕)
- 20本以上，享 8.5折
售價
$
洽詢
- 一般書籍
- ISBN：9780071086189
- 作者：Steven C. Chapra
- 版次：3
- 年份：2012
- 出版商：McGraw-Hill
- 頁數/規格：653頁/平裝雙色
書籍介紹
本書特色
目錄
作者介紹
Description
Steven Chapra's Applied Numerical Methods with MATLAB, third edition, is written for engineering and science students who need to learn numerical problem solving. Theory is introduced to inform key concepts which are framed in applications and demonstrated using MATLAB. The book is designed for a one-semester or one-quarter course in numerical methods typically taken by undergraduates.
The third edition features new chapters on Eigenvalues and Fourier Analysis and is accompanied by an extensive set of m-files and instructor materials.
Steven Chapra's Applied Numerical Methods with MATLAB, third edition, is written for engineering and science students who need to learn numerical problem solving. Theory is introduced to inform key concepts which are framed in applications and demonstrated using MATLAB. The book is designed for a one-semester or one-quarter course in numerical methods typically taken by undergraduates.
The third edition features new chapters on Eigenvalues and Fourier Analysis and is accompanied by an extensive set of m-files and instructor materials.
Features
- Updated Coverage 30% of the problems are new, and many examples have been added. Many important MATLAB functions are explained in context.
- Engineering Examples, case studies, and applications are presented throughout the text and cover the many engineering disciplines. The level of mathematical rigor is appropriate for students at this level.
- MATLAB m-files Examples and problems are integrated with MATLAB M-files, and relevant MATLAB functions are introduced in each chapter. These files are available on the McGraw-Hill companion website as well as the MATLAB website.
- Two New Chapters Chapter 13-Eigenvalues, and Chapter 16-Fast Fourier Transform have been added in response to instructor requests.
- Companion Website contains the instructor's solutions manual, PowerPoint lecture slides, and MATLAB M-files.
- To purchase an electronic eBook version of this title visit www.CourseSmart.com (ISBN 9780077352998). With the CourseSmart eTextbook version of this title, students can save money, reduce their impact on the environment, and access powerful web tools for learning. Faculty can also review and compare the full text online without having to wait for a print desk copy.
Table of Contents
Part One: Modeling, Computers, and Error Analysis
Chapter 1: Mathematical Modeling, Numerical Methods and Problem Solving
Chapter 2: MATLAB Fundamentals
Chapter 3: Programming with MATLAB
Chapter 4: Roundoff and Truncation Errors
Part Two: Roots and Optimization
Chapter 5: Roots: Bracketing Methods
Chapter 6: Roots: Open Methods
Chapter 7: Optimization
Part Three: Linear Systems
Chapter 8: Linear Algebraic Equations and Matrices
Chapter 9: Gauss Elimination
Chapter 10: LU Factorization
Chapter 11: Matrix Inverse and Condition
Chapter 12: Iterative Methods
Chapter 13: Eigenvalues
Part Four: Curve Fitting
Chapter 14: Linear Regression
Chapter 15: General Linear Least-Squares and Nonlinear Regression
Chapter 16: Fourier Analysis
Chapter 17: Polynomial Interpolation
Chapter 18: Splines and Piecewise Interpolation
Part Five: Integration and Differentiation
Chapter 19: Numerical Integration Formulas
Chapter 20: Numerical Integration of Functions
Chapter 21: Numerical Differentiation
Part Six: Ordinary Differential Equations
Chapter 22: Initial-Value Problems
Chapter 23: Adaptive Methods and Stiff Systems
Chapter 24: Boundary-Value Problems
Part One: Modeling, Computers, and Error Analysis
Chapter 1: Mathematical Modeling, Numerical Methods and Problem Solving
Chapter 2: MATLAB Fundamentals
Chapter 3: Programming with MATLAB
Chapter 4: Roundoff and Truncation Errors
Part Two: Roots and Optimization
Chapter 5: Roots: Bracketing Methods
Chapter 6: Roots: Open Methods
Chapter 7: Optimization
Part Three: Linear Systems
Chapter 8: Linear Algebraic Equations and Matrices
Chapter 9: Gauss Elimination
Chapter 10: LU Factorization
Chapter 11: Matrix Inverse and Condition
Chapter 12: Iterative Methods
Chapter 13: Eigenvalues
Part Four: Curve Fitting
Chapter 14: Linear Regression
Chapter 15: General Linear Least-Squares and Nonlinear Regression
Chapter 16: Fourier Analysis
Chapter 17: Polynomial Interpolation
Chapter 18: Splines and Piecewise Interpolation
Part Five: Integration and Differentiation
Chapter 19: Numerical Integration Formulas
Chapter 20: Numerical Integration of Functions
Chapter 21: Numerical Differentiation
Part Six: Ordinary Differential Equations
Chapter 22: Initial-Value Problems
Chapter 23: Adaptive Methods and Stiff Systems
Chapter 24: Boundary-Value Problems
Steven C. Chapra, Tufts University
