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 Jeffrey R. Chasnov - Harvey Mudd College
This course consists of both numerical methods and computational physics. MATLAB is used to solve various computational math problems. The course is primarily for Math majors and supposes no previous knowledge of numerical analysis or methods.
by Hans Petter Langtangen, Svein Linge - Springer
This easy-to-read book introduces the basics of solving partial differential equations by means of finite difference methods. Unlike many of the traditional academic works on the topic, this book was written for practitioners.
by James M. McDonough - University of Kentucky
These notes cover the following topics: Numerical linear algebra; Solution of nonlinear equations; Approximation theory; Numerical solution of ordinary differential equations; Numerical solution of partial differential equations.
by George Benthien
Tutorial discussing some of the numerical aspects of practical harmonic analysis. Topics include Historical Background, Fourier Series and Integral Approximations, Convergence Improvement, Differentiation of Fourier Series and Sigma Factors, etc.