Applied Numerical Methods for Engineers Using MATLAB and C

ISBN-10: 0534370144

ISBN-13: 9780534370145

Edition: 2000

List price: $182.95 Buy it from $21.60 Rent it from $39.98
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This book provides a comprehensive discussion of numerical computing techniques with an emphasis on practical applications in the fields of civil, chemical, electrical, and mechanical engineering. It features two software libraries that implement the algorithms developed in the text - a MATLAB toolbox, and an ANSI C library. This book is intended for undergraduate students. Each chapter includes detailed case study examples from the four engineering fields with complete solutions provided in MATLAB and C, detailed objectives, numerous worked-out examples and illustrations, and summaries comparing the numerical techniques. Chapter problems are divided into separate analysis and computation sections. Documentation for the software is provided in text appendixes that also include a helpful review of vectors and matrices. The Instructor's Manual includes a disk with software documentation and complete solutions to both problems and examples in the book.
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Book details

List price: $182.95
Copyright year: 2000
Publisher: Course Technology
Publication date: 9/16/1999
Binding: Hardcover
Pages: 740
Size: 7.50" wide x 9.25" long x 1.25" tall
Weight: 2.838
Language: English

Sandra L. Harris is Associate Professor of Chemical Engineering at Clarkson University. Dr. Harris teaching interests include process control, thermodynamics, and biochemical engineering. Her research interests are centered on periodic processing, control of systems having varying dead times, and generation of input signals for efficient process identification.

Numerical Computation Motivation and Objectives
Number Representation
Machine Precision
Round-Off Error
Truncation Error
Random Number Generation
Numerical Software
Chapter Summary
Linear Algebraic Systems Motivation and Objectives
Gauss-Jordan Elimination
Gaussian Elimination
LU Decomposition
Ill-Conditioned Systems
Iterative Methods
Chapter Summary
Eigenvalues and Eigenvectors Motivation and Objectives
The Characteristic Polynomial
Power Methods
Jacobi''s Method
Householder Transformation
QR Method
Danilevsky''s Method
Polynomial Roots
Chapter Summary
Curve Fitting Motivation and Objectives
Newton''s Difference Formula
Cubic Splines
Least Square
Two-Dimensional Interpolation
Chapter Summary
Root Finding Motivation and Objectives
Bracketing Methods
Contraction Mapping Method
Secant Method
Muller''s Method
Newton''s Method
Polynomial Roots
Nonlinear Systems of Equations
Chapter Summary
Optimization Motivation and Objectives
Local and Global Minima
Line Searches
Steepest Descent Method
Conjugate-Gradient Method
Quasi-Newton Methods
Penalty Functions
Simulated Annealing
Chapter Summary
Differentiation and Integration Motivation and Objectives
Numerical Differentiation
Noise-Corrupted Data
Newton-Cotes Integration Formulas
Romberg Integration
Gauss Quadrature
Improper Integrals
Multiple Integrals
Chapter Summary
Ordinary Differential Equations Motivation and Objectives
Euler''s Method
Runge-Kutta Methods
Step Size Control
Multi-Step Methods
Bulirsch-Stoer Extrapolation Methods
Stiff Differential Equations
Boundary Value Problems
Partial Differential Equations Motivation and Objectives
Elliptic Equations
One-Dimensional Parabolic Equations
Two-Dimensional Parabolic Equations
One-Dimensional Hyperbolic Equations
Two-Dimensional Hyperbolic Equations
Chapter Summary
Digital Signal Processing Motivation and Objectives
Fourier Transform
Fast Fourier Transform (FFT)
Convolution Digital Filters
Two-Dimensional FFT
System Identification
Chapter Summary
References And Further Reading
Nlib Using Matlab?
A Numerical Toolbox: NLIB
Main-Program Support
Linear Algebraic Systems
Eigenvalues and Eigenvectors
Curve Fitting
Root Finding
Differentiation and Integration
Ordinary Differential Equations
Partial Differential Equations
Digital Signal Processing
Nlib Using C
A Numerical Library: NLIB
NLIB Data Types
NLIB Core: nlib.c
Tabular Display: show.c
Graphical Display: draw.c
Linear Algebraic Systems: linear.c
Eigenvalues and Eigenvectors: eigen.c
Curve Fitting: curves.c
Root Finding: roots.c
Optimization: optim.c
Differentiation and Integration: integ.c
Ordinary Differential Equations: ode.c
Partial Differential Equations: pde.c
Digital Signal Processing: dsp.c
Vectors and Matrices
Vector and Matrix Notation
Basic Operations
Eigenvalues and Eigenvectors
Vector Norms
Answers to Selected Problems
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