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A continuation of 200-level linear algebra with computational and theoretical aspects and applications.
This course looks at how matrix algebra can be applied to solve a variety of important problems in commerce, engineering, and elsewhere. Emphasis is on numerically stable solution methods, including via elementary orthogonal matrices. Linear programming is examined in depth. Topics covered: Vector and matrix norms, condition number, Householder and Givens matrices, QR and rank 1 updates to QR, least squares and shortest solutions, Schur theorem, eigenvalue deflation, singular value decomposition, Moore-Penrose pseudo-inverse, linear programming, revised simplex, artificial variables, shadow prices, duality, degeneracy, Sherman-Morrison formula, positive definiteness and the modified Cholesky factorization, equality constrained quadratic programming.Applications:Outlier insensitive and infinity norm data fitting, total least squares, image processing, minimum energy flows, applications of linear programming including blending, transportation, resource allocation, and rostering.
At the end of this course successful students will:Be proficient in the methods and applications listed aboveUnderstand the theoretical basis for the topics in the courseBe able to use these methods in a variety of applications, including via MATLABBe able to construct a mathematical model of a standard problem, and interpret the model’s solution in the context of the applicationHave developed communication and problem solving skills, including as a team.
(MATH251 and MATH252), MATH254, EMTH204, MATH203, EMTH203 or EMTH211.
MATH352, EMTH412
Christopher Price
MATH303 Homepage General information for students Library portal LEARN
Domestic fee $672.00
International fee $3,388.00
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Mathematics and Statistics .