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 Ian Craw - University of Aberdeen
The overall aim of the course is to present modern computer programming techniques in the context of mathematical computation and numerical analysis and to foster the independence needed to use these techniques as appropriate in subsequent work.
by Yousef Saad - SIAM
This book discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods for solving matrix eigenvalue problems that arise in various engineering applications.
by C.T. Kelley - SIAM
This book focuses on a small number of methods and treats them in depth. The author provides a complete analysis of the conjugate gradient and generalized minimum residual iterations as well as recent advances including Newton-Krylov methods.
by Douglas W. Harder, Richard Khoury - University of Waterloo
Contents: Error Analysis, Numeric Representation, Iteration, Linear Algebra, Interpolation, Least Squares, Taylor Series, Bracketing, The Five Techniques, Root Finding, Optimization, Differentiation, Integration, Initial-value Problems, etc.