Author(s) : Steven C.Chapra
Publisher : McGraw Hill
Edition : Third
Pages : 673
size : 7.45 Mb
Book Review :
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.
TABLE OF CONTENTS
Part one: Modeling, Computers, and Error Analysis
1. Mathematical Modeling, Numerical Methods, and Problem Solving
2. MATLAB Fundamentals
3. Programming with MATLAB
4. Roundoff and Truncation Errors
Part two: Roots and Optimization
5. Roots: Bracketing Methods
6. Roots: Open Methods
7. Optimization
Part three: Linear Systems
8. Linear Algebraic Equations and Matrices
9. Gauss Elimination
10. LU Factorization
11. Matrix Inverse and Condition
12. Iterative Methods
13. Eigenvalues
Part four: Curve Fitting
14. Linear Regression
15. General Linear Least-Squares and Nonlinear Regression
16. Fourier Analysis
17. Polynomial Interpolation
18. Splines and Piecewise Interpolation
Part five: Integration and Differentiation
19. Numerical Integration Formulas
20. Numerical Integration of Functions
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 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.
TABLE OF CONTENTS
Part one: Modeling, Computers, and Error Analysis
1. Mathematical Modeling, Numerical Methods, and Problem Solving
2. MATLAB Fundamentals
3. Programming with MATLAB
4. Roundoff and Truncation Errors
Part two: Roots and Optimization
5. Roots: Bracketing Methods
6. Roots: Open Methods
7. Optimization
Part three: Linear Systems
8. Linear Algebraic Equations and Matrices
9. Gauss Elimination
10. LU Factorization
11. Matrix Inverse and Condition
12. Iterative Methods
13. Eigenvalues
Part four: Curve Fitting
14. Linear Regression
15. General Linear Least-Squares and Nonlinear Regression
16. Fourier Analysis
17. Polynomial Interpolation
18. Splines and Piecewise Interpolation
Part five: Integration and Differentiation
19. Numerical Integration Formulas
20. Numerical Integration of Functions
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
