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Numerical Analysis with CD-ROM

By Timothy Sauer

ISBN-10: 0-321-26898-9

ISBN-13: 978-0-321-26898-3What's this?

Published by Pearson

Pub. Date: Dec 7, 2005

Format: Cloth

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Student Solutions Manual

ISBN-10: 0-321-28686-3

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Table of Contents

CHAPTER 0. Fundamentals

0.1 Evaluating a polynomial

0.2 Binary numbers

0.2.1 Decimal to binary

0.2.2 Binary to decimal

0.3 Floating point representation of real numbers

0.3.1 Floating point formats

0.3.2 Machine representation

0.3.3 Addition of floating point numbers

0.4 Loss of significance

0.5 Review of calculus

0.6 Software and Further Reading

 

CHAPTER 1. Solving Equations

1.1 The Bisection Method

1.1.1 Bracketing a root

1.1.2 How accurate and how fast?

1.2 Fixed point iteration

1.2.1 Fixed points of a function

1.2.2 Geometry of Fixed Point Iteration

1.2.3 Linear Convergence of Fixed Point Iteration

1.2.4 Stopping criteria

1.3 Limits of accuracy

1.3.1 Forward and backward error

1.3.2 The Wilkinson polynomial

1.3.3 Sensitivity and error magnification

1.4 Newton’s Method

1.4.1 Quadratic convergence of Newton’s method

1.4.2 Linear convergence of Newton’s method

1.5 Root-finding without derivatives

1.5.1 Secant method and variants

1.5.2 Brent’s Method

REALITY CHECK 1: Kinematics of the Stewart platform

1.6 Software and Further Reading

 

CHAPTER 2. Systems of Equations

2.1 Gaussian elimination

2.1.1 Naive Gaussian elimination

2.1.2 Operation counts

2.2 The LU factorization

2.2.1 Backsolving with the LU factorization

2.2.2 Complexity of the LU factorization

2.3 Sources of error

2.3.1 Error magnification and condition number

2.3.2 Swamping

2.4 The PA=LU factorization

2.4.1 Partial pivoting

2.4.2 Permutation matrices

2.4.3 PA = LU factorization

2.4.4 Matlab commands for linear systems

2.5 Iterative methods

2.5.1 Jacobi Method

2.5.2 Gauss-Seidel Method and SOR

2.5.3 Convergence of iterative methods

2.5.4 Sparse matrix computations

REALITY CHECK 2: The Euler-Bernoulli Beam

2.6 Conjugate Gradient Method

2.6.1 Positive-definite matrices

2.6.2 Conjugate Gradient Method

2.7 Nonlinear systems of equations

2.7.1 Multivariate Newton’s method

2.7.2 Broyden’s method

2.8 Software and Further Reading

 

CHAPTER 3. Interpolation

3.1 Data and interpolating functions

3.1.1 Lagrange interpolation

3.1.2 Newton’s divided differences

3.1.3 How many degree d polynomials pass through n points?

3.1.4 Code for interpolation

3.1.5 Representing functions by approximating polynomials

3.2 Interpolation error

3.2.1 Interpolation error formula

3.2.2 Proof of Newton form and error formula

3.2.3 Runge phenomenon

3.3 Chebyshev interpolation

3.3.1 Chebyshev’s Theorem

3.3.2 Chebyshev polynomials

3.3.3 Change of interval

3.4 Cubic splines

3.4.1 Properties of splines

3.4.2 Endpoint conditions

3.5 B´ezier curves

REALITY CHECK 3: Constructing fonts from B´ezier splines

3.6 Software and Further Reading

 

CHAPTER 4. Least Squares

4.1 Inconsistent systems of equations

4.2 Linear and nonlinear models

4.2.1 Periodic data

4.2.2 Data linearization

4.3 QR factorization

4.3.1 Gram-Schmidt orthogonalization and least squares

4.3.2 Householder reflectors

4.4 Nonlinear least squares

4.4.1 Gauss-Newton method

4.4.2 Models with nonlinear coefficients

REALITY CHECK 4: GPS, conditioning and nonlinear least squares

4.5 Software and Further Reading

 

CHAPTER 5. Numerical Differentiation and Integration

5.1 Numerical differentiation

5.1.1 Finite difference formulas

5.1.2 Rounding error

5.1.3 Extrapolation

5.1.4 Symbolic differentiation and integration

5.2 Newton-Cotes formulas for numerical integration

5.2.1 Three simple integrals for Newton-Cotes Formulas

5.2.2 Trapezoid rule

5.2.3 Simpson’s Rule

5.2.4 Composite Newton-Cotes Formulas

5.2.5 Open Newton-Cotes methods

5.3 Romberg integration

5.4 Adaptive quadrature

5.5 Gaussian quadrature

REALITY CHECK 5: Motion control in computer-aided modelling

5.6 Software and Further Reading

 

CHAPTER 6. Ordinary Differential Equations

6.1 Initial value problems

6.1.1 Euler’s method

6.1.2 Existence, uniqueness, and continuity for solutions

6.1.3 First-order linear equations

6.2 Analysis of IVP solvers

6.2.1 Local and global truncation error

6.2.2 The explicit trapezoid method

6.2.3 Taylor methods

6.3 Systems of ordinary differential equations

6.3.1 Higher order equations

6.3.2 The pendulum

6.3.3 Orbital mechanics

6.4 Runge-Kutta methods and applications

6.4.1 Classical examples

REALITY CHECK 6: The Tacoma Narrows Bridge

6.5 Variable step-size methods

6.6 Implicit methods and stiff equations

6.7 Multistep methods

6.7.1 Generating multistep methods

6.7.2 Explicit multistep methods

6.7.3 Implicit multistep methods

6.8 Software and Further Reading

 

CHAPTER 7. Boundary Value Problems

7.1 Solutions of boundary value problems

7.1.1 Shooting method

REALITY CHECK 7: Buckling of a circular ring

7.2 Finite difference methods

7.2.1 Linear boundary value problems

7.2.2 Nonlinear boundary value problems

7.3 Collocation and the Finite Element Method

7.3.1 Collocation

7.3.2 Finite elements and the Galerkin method

7.4 Software and Further Reading

 

CHAPTER 8. Partial Differential Equations

8.1 Parabolic equations

8.1.1 Forward difference method

8.1.2 Stability analysis of forward difference method

8.1.3 Backward difference method

8.1.4 Crank-Nicolson method

8.2 Hyperbolic equations

8.3 Elliptic equations

8.3.1 Finite difference method for elliptic equations

REALITY CHECK 8: Heat distribution on a cooling fin

8.3.2 Finite element method for elliptic equations

8.4 Software and Further Reading

 

CHAPTER 9. Random Numbers and Applications

9.1 Random numbers

9.1.1 Pseudo-random numbers

9.2 Monte-Carlo simulation

9.2.1 Power laws for Monte Carlo estimation

9.2.2 Quasi-random numbers

9.3 Discrete and continuous Brownian motion

9.3.1 Random walks

9.3.2 Continuous Brownian motion

9.4 Stochastic differential equations

9.4.1 Adding noise to ODEs

9.4.2 Numerical methods for SDEs

REALITY CHECK 9: The Black-Scholes formula

9.5 Software and Further Reading

 

CHAPTER 10. Trigonometric Interpolation and the FFT

10.1 The Fourier Transform

10.1.1 Complex arithmetic

10.1.2 Discrete Fourier Transform

10.1.3 The Fast Fourier Transform

10.2 Trigonometric interpolation

10.2.1 The DFT Interpolation Theorem

10.2.2 Orthogonality and interpolation

10.2.3 Least squares fitting with trigonometric functions

10.2.4 Sound, noise, and filtering

REALITY CHECK 10: The Wiener filter

10.3 Software and Further Reading

 

CHAPTER 11. Compression

11.1 The Discrete Cosine Transform

11.1.1 One-dimensional DCT

11.2 Two-dimensional DCT and image compression

11.2.1 The two-dimensional Discrete Cosine Transform

11.2.2 Image compression

11.2.3 Quantization

11.3 Huffman coding

11.3.1 Information theory and coding

11.3.2 Huffman coding for the JPEG format

11.4 Modified DCT and sound compression

11.4.1 Modified Discrete Cosine Transform

11.4.2 Bit quantization

REALITY CHECK 11: A simple audio codec using the MDCT

11.5 Software and Further Reading

 

CHAPTER 12. Eigenvalues and Singular Values

12.1 Power iteration methods

12.1.1 Power iteration

12.1.2 Convergence of power iteration

12.1.3 Inverse power iteration

12.1.4 Rayleigh quotient iteration

12.2 QR algorithm

12.2.1 Simultaneous iteration

12.2.2 Real Schur form and QR

12.2.3 Householder reflectors

12.2.4 Upper Hessenberg form

REALITY CHECK 12: How search engines rate page quality

12.3 Singular value decomposition

12.3.1 Finding the SVD in general

12.3.2 Special case: symmetric matrices

12.4 Applications of the SVD

12.4.1 Properties of the SVD

12.4.2 Dimension reduction

12.4.3 Compression

12.4.4 Calculating the SVD

12.5 Software and Further Reading

 

CHAPTER 13. Optimization

13.1 Unconstrained optimization without derivatives

13.1.1 Golden section search

13.1.2 Successive parabolic interpolation

13.1.3 Nelder-Mead search

13.2 Unconstrained optimization with derivatives

13.2.1 Newton’s method

13.2.2 Steepest descent

13.2.3 Conjugate gradient search

13.2.4 Nonlinear least squares

REALITY CHECK 13: Molecular conformation and numerical optimization

13.3 Software and Further Reading

 

APPENDIX

Appendix A: Matrix Algebra

A.1 Matrix fundamentals

A.2 Block multiplication

A.3 Eigenvalues and eigenvectors

A.4 Symmetric matrices

A.5 Vector calculus

 

Appendix B: Introduction to Matlab

B.1 Starting Matlab

B.2 Matlab graphics

B.3 Programming in Matlab

B.4 Flow control

B.5 Functions

B.6 Matrix operations

B.7 Animation

 

Answers to Selected Exercises

 

Index

 

Bibliography

 

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