Courses Handbook 2006 - [Archived]

308690 (v.1) Computational Mathematics 301


Area:

Department of Mathematics and Statistics

Credits:

25.0

Contact Hours:

4.0
 
** The tuition pattern below provides details of the types of classes and their duration. This is to be used as a guide only. For more precise information please check your unit outline. **
 

Lecture:

1 x 3 Hours Weekly

Tutorial:

1 x 1 Hours Weekly

Prerequisite(s):

4515 (v.5) Scientific Computing 201 or any previous version
 

Syllabus:

Numerical methods for initial-value problems and multi-step methods. Systems of ordinary differential equations. Two-point boundary value problems, finite difference and shooting methods. Iterative methods for large-scale linear systems of equations, Jacobi, Gauss-Seidel and SOR methods, convergence and error bounds. Non-linear systems of equations and Newton's Method. Introduction to Partial Differential Equations and second-order finite difference methods. Approximation Theory - weighted least squares approximation, orthogonal polynomials, Chebyshev approximation and Remez Algorithm. Splines - natural cubic splines.
 
** To ensure that the most up-to-date information about unit references, texts and outcomes appears, they will be provided in your unit outline prior to commencement. **
 

Field of Education:

010101 Mathematics

Funding Cluster:

04 - Mathematics, Statistics

SOLT (Online) Definitions*:

Not Online
*Extent to which this unit or thesis utilises online information

Result Type:

Grade/Mark

Availability

Availability Information has not been provided by the respective School or Area. Prospective students should contact the School or Area listed above for further information.

 
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