Numerical Analysis and Graphic Visualization with MATLAB

Numerical Analysis and Graphic Visualization with MATLAB

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For courses in numerical methods.

MATLAB has changed the concept of programming for numerical and mathematical analyses, and in doing so offers unique and fascinating capabilities in the engineering and science fields. This text fully implements MATLAB's mathematical and graphic tools in application of numerical analysis. The author covers programming in MATLAB, mathematical basics of numerical analysis, application of numerical methods to engineering, scientific, and mathematical problems, and scientific graphics with MATLAB.
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Product details

  • Hardback | 544 pages
  • 180.3 x 243.8 x 25.4mm | 975.23g
  • Prentice Hall
  • Upper Saddle River, United States
  • English
  • 2nd edition
  • w. figs.
  • 0130654892
  • 9780130654892

Back cover copy

Leverage the power of MATLAB 6 in all your technical computation and measurement applications

Now, there is a complete introduction to numerical methods and visualization with the latest, most powerful version of MATLAB, Version 6.0. Dr. Shoichiro Nakamura introduces the skills and knowledge needed to solve numerical equations with MATLAB, understand the computational results, and present them graphically.

This book brings together all four cornerstones of numerical analysis with MATLAB: the fundamental techniques of MATLAB programming; the mathematical basis of numerical methods; the application of numerical analysis to engineering, scientific, and mathematical problems; and the creation of scientific graphics. Coverage includes:

Complete introductory tutorials for both MATLAB 6.0 programming and professional-quality 3D graphicsLinear algebra applications: matrices, vectors, Gauss elimination, Gauss-Jordan elimination, LU decomposition, and morePolynomials and interpolation, including interpolation with Chebyshev points; cubic hermite, 2D and transfinite interpolation; and M-filesNumerical integration, differentiation, and roots of nonlinear equationsAdvanced techniques, including curve fitting, spline functions, and boundary value problems

Whether you are a student, engineer, scientist, researcher, or economic analyst, MATLAB 6 offers you unprecedented power for defining and solving problems. Put that power to work -- with Numerical Analysis and Graphical Visualization with MATLAB, second edition.
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Table of contents


1. MATLAB Primer.

Before Starting Calculations. How to Do Calculations. Branch Statements. Loops with for/end or while/end. Reading and Writing. Array Variables. Unique Aspect of Numbers in MATLAB. Mathematical Functions of MATLAB. Functions That Do Chores. Developing a Program as an M-File. How to Write Your Own Functions. Saving and Loading Data. How to Make Hard Copies.

2. Graphics with MATLAB.

Simple Plotting. Interactive Editing of Figures. How to Print or Record Graphs. Plotting of Two-Dimensional Functions. Triangular Grid and Contours. Curvilinear Grid and Contours. Plotting Curved Surfaces. MATLAB as a Drawing Board. Interactive Graphics. M-Files.

3. Linear Algebra.

Matrices and Vectors. Matrix and Vector Operations in MATLAB. Inverse Matrix. Linear Equations. Unsolvable Problems. The Determinant. Ill-conditioned Problems. Gauss Elimination. Gauss-Jordan Elimination and Matrix Inversion. LU Decomposition. Iterative Solution. Matrix Eigenvalues.

4. Polynomials and Interpolation.

MATLAB Commands for Polynomials. Linear Interpolation. Polynomial Interpolation with Power Series. Lagrange Interpolation Polynomial. Error of Interpolation Polynomials. Differentiation and Integration of Lagrange Interpolation Formula. Interpolation with Chebyshev Points. Cubic Hermite Interpolation. Two-Dimensional Interpolation. Transfinite Interpolation. M-Files.

5. Numerical Integration.

Trapezoidal Rule. Simpson's Rules. Other Quadratures. Numerical Integration with Infinite Limits or Singularities. MATLAB Commands for Integrations. Numerical Integration on a Two-Dimensional Domain. M-Files.

6. Numerical Differentiation.

Derivatives of Interpolation Polynomials. Difference Approximations. Taylor Expansion Method. Algorithms to Automate Derivations. Difference Approximation for Partial Derivatives. Numerical Evaluation of High-Order Derivatives. M-Files.

7. Roots of Nonlinear Equations.

Graphical Method. Bisection Method. Newton Iteration. Secant Method. Successive Substitution Method. Simultaneous Nonlinear Equations. M-Files.

8. Curve Fitting To Measured Data.

Line Fitting. Nonlinear Curve Fitting with a Power Function. Curve Fitting with a Higher-Order Polynomial. Curve Fitting by a Linear Combination of Known Functions.

9. Spline Functions and Nonlinear Interpolation.

C-Spline Interpolation. Cubic B-Spline. Interpolation with a Nonlinear Function. M-Files.

10. Initial-Value Problems of Ordinary Differential Equations.

First-Order ODEs. Euler Methods. Runge-Kutta Methods. Shooting Method. Method of Lines.

11. Boundary-Value Problems of Ordinary Differential Equations.

Introduction. Boundary-Value Problems for Rods and Slabs. Solution of Tridiagonal Equations. Variable Coefficients and Nonuniform Grids. Cylinders and Spheres. Nonlinear Ordinary Differential Equations.

Appendix A: Colors.

Appendix B: Drawing Three-Dimensional Objects.

Appendix C: Movies.

Appendix D: Image Processing.

Appendix E: Graphical User Interface.

Appendix F: Answer Key.

Subject Index.
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About Shoichiro Nakamura

SHOICHIRO NAKAMURA is Professor at Ohio State. His current research interests include computational simulation of blood flows in artificial heart pumps, polymer flows in plastic processing, and internal and external automobile aerodynamics, as well as numerical methods for supercomputers. He holds a Ph.D. from Kyoto University, Japan.
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