Numerical Linear Approximation in C
Illustrating the relevance of linear approximation in a variety of fields, Numerical Linear Approximation in C presents a unique collection of linear approximation algorithms that can be used to analyze, model, and compress discrete data. Developed by the lead author, the algorithms have been successfully applied to several engineering projects at the National Research Council of Canada.

Basing most of the algorithms on linear programming techniques, the book begins with an introductory section that covers applications, the simplex method, and matrices. The next three parts focus on various L1, Chebyshev, and least squares approximations, including one-sided, bounded variables, and piecewise. The final section presents the solution of underdetermined systems of consistent linear equations that are subject to different constraints on the elements of the unknown solution vector.

Except in the preliminary section, all chapters include the C functions of the algorithms, along with drivers that contain numerous test case examples and results. The accompanying CD-ROM also provides the algorithms written in C code as well as the test drivers. To use the software, it is not required to understand the theory behind each function.

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Numerical Linear Approximation in C
Illustrating the relevance of linear approximation in a variety of fields, Numerical Linear Approximation in C presents a unique collection of linear approximation algorithms that can be used to analyze, model, and compress discrete data. Developed by the lead author, the algorithms have been successfully applied to several engineering projects at the National Research Council of Canada.

Basing most of the algorithms on linear programming techniques, the book begins with an introductory section that covers applications, the simplex method, and matrices. The next three parts focus on various L1, Chebyshev, and least squares approximations, including one-sided, bounded variables, and piecewise. The final section presents the solution of underdetermined systems of consistent linear equations that are subject to different constraints on the elements of the unknown solution vector.

Except in the preliminary section, all chapters include the C functions of the algorithms, along with drivers that contain numerous test case examples and results. The accompanying CD-ROM also provides the algorithms written in C code as well as the test drivers. To use the software, it is not required to understand the theory behind each function.

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Numerical Linear Approximation in C

Numerical Linear Approximation in C

Numerical Linear Approximation in C

Numerical Linear Approximation in C

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Overview

Illustrating the relevance of linear approximation in a variety of fields, Numerical Linear Approximation in C presents a unique collection of linear approximation algorithms that can be used to analyze, model, and compress discrete data. Developed by the lead author, the algorithms have been successfully applied to several engineering projects at the National Research Council of Canada.

Basing most of the algorithms on linear programming techniques, the book begins with an introductory section that covers applications, the simplex method, and matrices. The next three parts focus on various L1, Chebyshev, and least squares approximations, including one-sided, bounded variables, and piecewise. The final section presents the solution of underdetermined systems of consistent linear equations that are subject to different constraints on the elements of the unknown solution vector.

Except in the preliminary section, all chapters include the C functions of the algorithms, along with drivers that contain numerous test case examples and results. The accompanying CD-ROM also provides the algorithms written in C code as well as the test drivers. To use the software, it is not required to understand the theory behind each function.


Product Details

ISBN-13: 9781584889793
Publisher: CRC Press
Publication date: 05/19/2008
Series: Chapman & Hall/CRC Numerical Analysis and Scientific Computing Series
Sold by: Barnes & Noble
Format: eBook
Pages: 968
File size: 5 MB

About the Author

Abdelmalek, Nabih; Malek, William A.

Table of Contents

Preliminaries and Tutorials
Applications of Linear Approximation
Applications to social sciences and economics
Applications to industry
Applications to digital images
Preliminaries
Discrete linear approximation and solution of overdetermined linear equations
Comparison between the L1, the L2, and the L norms by a practical example
Error tolerances in the calculation
Representation of vectors and matrices in C
Outliers and dealing with them
Linear Programming and the Simplex Algorithm
Notations and definitions
The simplex algorithm
The simplex tableau
The two-phase method
Duality theory in linear programming
Degeneracy in linear programming and its resolution
Linear programming and linear approximation
Stability of the solution in linear programming
Efficient Solutions of Linear Equations
Vector and matrix norms and relevant theorems
Elementary matrices
Gauss LUdecomposition with complete pivoting
Orthogonal factorization methods
Gauss–Jordan method
Rounding errors in arithmetic operations
The L1 Approximation
Linear L1 Approximation
Linear programming formulation of the problem
Description of the algorithm
The dual simplex method
Modification to the algorithm
Occurrence of degeneracy
A significant property of the L1 approximation
Triangular decomposition of the basis matrix
Arithmetic operations count
Numerical results and comments
C source code
One-Sided L1 Approximation
A special problem of a general constrained one
Linear programming formulation of the problem
Description of the algorithm
Numerical results and comments
C source code
L1 Approximation with Bounded Variables
A special problem of a general constrained one
Linear programming formulation of the problem
Description of the algorithm
Numerical results and comments
C source code
L1 Polygonal Approximation of Plane Curves
Approaches to polygonal approximation
The L1 approximation problem
Description of the algorithm
Linear programming technique
Numerical results and comments
C source code
Piecewise L1 Approximation of Plane Curves
Characteristics of the piecewise approximation
The discrete linear L1 approximation problem
Description of the algorithms
Numerical results and comments
C source code
The Chebyshev Approximation
Linear Chebyshev Approximation
Linear programming formulation of the problem
Description of the algorithm
A significant property of the Chebyshev approximation
Numerical results and comments
C source code
One-Sided Chebyshev Approximation
A special problem of a general constrained one
Linear programming formulation of the problem
Description of the algorithm
Numerical results and comments
C source code
Chebyshev Approximation with Bounded Variables
A special problem of a general constrained one
Linear programming formulation of the problem
Description of the algorithm
Numerical results and comments
C source code
Restricted Chebyshev Approximation
A special problem of general constrained algorithms
Linear programming formulation of the problem
Description of the algorithm
The triangular decomposition method
Arithmetic operations count
Numerical results and comments
C source code
Strict Chebyshev Approximation
The problem as presented by Descloux
Linear programming analysis of the problem
Numerical results and comments
C source code
Piecewise Chebyshev Approximation
Characteristic properties of piecewise approximation
The discrete linear Chebyshev approximation problem
Description of the algorithms
Numerical results and comments
C source code
Solution of Linear Inequalities
Pattern classification problem
Solution of the system of linear inequalities Ca > 0
Linear one-sided Chebyshev approximation algorithm
Linear one-sided L1 approximation algorithm
Numerical results and comments
C source code
The Least Squares Approximation
Least Squares and Pseudo-Inverses of Matrices
Least squares solution of linear equations
Factorization of matrix A
Explicit expression for the pseudo-inverse
The singular value decomposition (SVD)
Practical considerations in computing
Linear spaces and the pseudo-inverses
Multicollinearity, collinearity, or the ill-conditioning of matrix A
Principal components analysis (PCA)
Partial least squares method (PLS)
Ridge equation
Numerical results and comments
C source code
Piecewise Linear Least Squares Approximation
Characteristics of the approximation
The discrete linear least squares approximation problem
Description of the algorithms
Numerical results and comments
Updating and downdating techniques
C source code
Solution of Ill-Posed Linear Systems
Solution of ill-posed linear systems
Estimation of the free parameter
Description of the new algorithm
Optimum value of the rank
Use of linear programming techniques
Numerical results and comments
C source code
Solution of Underdetermined Systems Of Linear Equations
L1 Solution of Underdetermined Linear Equations
Linear programming formulation of the problem
Description of the algorithm
Numerical results and comments
C source code
Bounded and L1 Bounded Solutions of Underdetermined Linear Equations
Linear programming formulation of the two problems
Description of the algorithms
Numerical results and comments
C source code
Chebyshev Solution of Underdetermined Linear Equations
The linear programming problem
Description of the algorithm
Numerical results and comments
C source code
Bounded Least Squares Solution of Underdetermined Linear Equations
Quadratic programming formulation of the problems
Solution of problem (E0)
Solution of problem (E)
Numerical results and comments
C source code
Appendix A: References
Appendix B: Main Program
Appendix C: Constants, Types, and Function Prototypes
Appendix D: Utilities and Common Functions
Index
An Introduction appears at the beginning of each chapter.
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