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Numerical Methods for Engineers,9780073397924
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Numerical Methods for Engineers

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McGraw-Hill Science/Engineering/Math
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This is the 7th edition with a publication date of 1/24/2014.
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    Numerical Methods for Engineers


The seventh edition of Chapra and Canale's Numerical Methods for Engineers retains the instructional techniques that have made the text so successful. Chapra and Canale's unique approach opens each part of the text with sections called “Motivation,“ “Mathematical Background,” and “Orientation” Each part closes with an “Epilogue” containing “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. Helpful separate Appendices. “Getting Started with MATLAB” and “Getting Started with Mathcad” which make excellent references.

Numerous new or revised problems are drawn from actual engineering practice. The expanded breadth of engineering disciplines covered is especially evident in these exercises, which now cover such areas as biotechnology and biomedical engineering. Excellent new examples and case studies span all areas of engineering giving students a broad exposure to various fields in engineering.

Users will find use of files for many popular software packages, specifically MATLAB®, Excel® with VBA, and Mathcad®. There is also material on developing MATLAB® m-files and VBA macros.

Table of Contents

Part 1 Modeling, Computers, and Error Analysis

1 Mathematical Modeling and Engineering Problem Solving

2 Programming and Software

3 Approximations and Round-Off Errors

4 Truncation Errors and the Taylor Series

Part 2 Roots of Equations

5 Bracketing Methods

6 Open Methods

7 Roots of Polynomials

8 Case Studies: Roots of Equations

Part 3 Linear Algebraic Equations

9 Gauss Elimination

10 LU Decomposition and Matrix Inversion

11 Special Matrices and Gauss-Seidel

12 Case Studies: Linear Algebraic Equations

Part 4 Optimization

13 One-Dimensional Unconstrained Optimization

14 Multidimensional Unconstrained Optimization

15 Constrained Optimization

16 Case Studies: Optimization

Part 5 Curve Fitting

17 Least-Squares Regression

18 Interpolation

19 Fourier Approximation

20 Case Studies: Curve Fitting

Part 6 Numerical Differentiation and Integration

21 Newton-Cotes Integration Formulas

22 Integration of Equations

23 Numerical Differentiation

24 Case Studies: Numerical Integration and Differentiation

Part 7 Ordinary Differential Equations

25 Runge-Kutta Methods

26 Stiffness and Multistep Methods

27 Boundary-Value and Eigenvalue Problems

28 Case Studies: Ordinary Differential Equations

Part 8 Partial Differential Equations

29 Finite Difference: Elliptic Equations

30 Finite Difference: Parabolic Equations

31 Finite-Element Method

32 Case Studies: Partial Differential Equations

Appendix A The Fourier Series

Appendix B Getting Started with Matlab

Appendix C Getting Starte dwith Mathcad



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