Linear Optimisation and Numerical Analysis
by Ian Craw
Publisher: University of Aberdeen 2002
Number of pages: 151
The overall aim of the course is: to describe the simplex algorithm and show how it can be used to solve real problems; to show how previous results in linear algebra give a framework for understanding the simplex algorithm; and to place the simplex algorithm in a more general context by describing other calculus-based and computer based optimization algorithms.
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by Richard Barrett et al. - Society for Industrial Mathematics
The book focuses on the use of iterative methods for solving large sparse systems of linear equations. General and reusable templates are introduced to meet the needs of both the traditional user and the high-performance specialist.
by Steven E. Pav - University of California at San Diego
From the table of contents: A 'Crash' Course in octave/Matlab; Solving Linear Systems; Finding Roots; Interpolation; Spline Interpolation; Approximating Derivatives; Integrals and Quadrature; Least Squares; Ordinary Differential Equations.
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Using examples from a broad base of computational tasks, including data processing and computational photography, the book introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into theoretical tools.
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Tutorial describing many of the standard numerical methods used in Linear Algebra. Topics include Gaussian Elimination, LU and QR Factorizations, The Singular Value Decomposition, Eigenvalues and Eigenvectors via the QR Method, etc.