Courses Handbook 2007 - [ 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 successive over relaxation (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.

 
Curtin Search Curtin Site Index