Numerical Methods Using Matlab, 4th Edition

John H. Mathews all

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Numerical Methods Using Matlab, 4th Edition

By John H. Mathews, Kurtis K. Fink
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John H. Mathews all
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For undergraduate Introduction to Numerical Analysis courses in mathematics, science, and engineering departments.

This book provides a fundamental introduction to numerical analysis for undergraduate students in the areas of mathematics, computer science, physical sciences, and engineering. Knowledge of calculus is assumed.

  • Expanded emphasis on analysis of competing methods and issues of error.
    • Helps students understand that one can't rely blindly on a given numerical package.

  • Rewritten chapter on numerical optimisation.
    • Provides a presentation that flows more smoothly.

  • Topics for minimisation of z = f(x,y) are included.
    • Gives students a more thorough treatment that is useful here.

  • Projects for undergraduate library research experience have been added.
    • Provides students with opportunities for further study.

  • Explicit use of the software MATLAB is offered.
    • Builds on students' knowledge of structured programming and provides the opportunity to practice scientific programming.

  • Each numerical method is presented in a self-contained format.
    • Clearly explains numerical methods to students.

  • Balance of theory and application.
    • Builds on students' knowledge of calculus and basic linear algebra in a clear and readable presentation.

  • A variety of problems.
    • Sharpens students skills with extensive problem sets with a wide variety of activities.

  • A wealth of tables and graphs.
    • Illustrates computer calculations in examples making the resulting numerical approximations easier to interpret.

Table of contents
  • 1. Preliminaries.
  • 2. The Solution of Nonlinear Equations f (x) = 0.
  • 3. The Solution of Linear Systems AX = B.
  • 4. Interpolation and Polynomial Approximation.
  • 5. Curve Fitting.
  • 6. Numerical Differentiation.
  • 7. Numerical Integration.
  • 8. Numerical Optimization.
  • 9. Solution of Differential Equations.
  • 10. Solution of Partial Differential Equations.
  • 11. Eigenvalues and Eigenvectors.
  • Appendix: An Introduction to MATLAB.
  • Answers to Selected Exercises.
  • Index.