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DEGREE REGULATIONS & PROGRAMMES OF STUDY 2018/2019

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DRPS : Course Catalogue : School of Mathematics : Mathematics

Undergraduate Course: Numerical Linear Algebra (MATH10098)

Course Outline
SchoolSchool of Mathematics CollegeCollege of Science and Engineering
Credit level (Normal year taken)SCQF Level 10 (Year 3 Undergraduate) AvailabilityAvailable to all students
SCQF Credits10 ECTS Credits5
SummaryDriven by the needs of applications, this course studies reliable and computationally efficient numerical techniques for practical linear algebra problems. As well as traditional theoretical assessment of the techniques studied, Matlab is used to perform practical experiments to complement students' insight into the subject. As a consequence, in addition to the assessment of theoretical understanding and hand calculation via a closed book examination, the course is also assessed via a Matlab class test.
Course description Linear Algebra is one of the most widely used topics in the mathematical sciences. At level 8 or 9 students are taught standard techniques for basic linear algebra tasks including the solution of linear systems, finding eigenvalues/eigenvectors and orthogonalisation of bases. However, these techniques are usually computationally too intensive to be used for the large matrices encountered in practical applications. NLA will introduce students to these practical issues and will present, analyse, and apply algorithms for these tasks which are reliable and computationally efficient. The course includes significant lab work using Matlab and this is assessed in a class test. The theoretical material is assessed in a closed book examination.
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Introduction to Linear Algebra (MATH08057) OR Accelerated Algebra and Calculus for Direct Entry (MATH08062)
Co-requisites
Prohibited Combinations Students MUST NOT also be taking Numerical Linear Algebra and Applications (MATH10059) OR Numerical Linear Algebra and Applications (MATH11196)
Other requirements None
Information for Visiting Students
Pre-requisitesVisiting students are advised to check that they have studied the material covered in the syllabus of any pre-requisite course listed above before enrolling.
High Demand Course? Yes
Course Delivery Information
Academic year 2018/19, Available to all students (SV1) Quota:  None
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 100 ( Lecture Hours 18, Seminar/Tutorial Hours 5, Supervised Practical/Workshop/Studio Hours 12, Summative Assessment Hours 1.5, Programme Level Learning and Teaching Hours 2, Directed Learning and Independent Learning Hours 61 )
Assessment (Further Info) Written Exam 50 %, Coursework 50 %, Practical Exam 0 %
Additional Information (Assessment) Coursework 50%, Examination 50%
Feedback Not entered
Exam Information
Exam Diet Paper Name Hours & Minutes
Main Exam Diet S1 (December)Numerical Linear Algebra1:30
Learning Outcomes
On completion of this course, the student will be able to:
  1. Analyse and discuss the computational efficiency of numerical linear algebra methods for solving linear systems of equations and finding one or more eigenvalues and/or eigenvectors of a matrix, including the influence of sparsity.
  2. Discuss the implications of problem conditioning and the consequences of using floating-point arithmetic.
  3. Perform scientific investigation of method by implementing it and performing experiments in Matlab.
  4. Identify the need for numerical linear algebra techniques to solve subproblems for a range of applications.
Reading List
Numerical Linear Algebra and Applications, Second Edition", by B. N. Datta, SIAM, ISBN: 978-0-898716-85-6
Numerical Linear Algebra by Lloyd "Nick" Trefethen and David Bau III, SIAM, ISBN: 978-0898713619
Applied numerical linear algebra by James "Jim" Demmel, SIAM, ISBN: 978-0898713893
Additional Information
Graduate Attributes and Skills Not entered
KeywordsNLA,numerical methods,linear algebra,matlab
Contacts
Course organiserDr Aretha Teckentrup
Tel: (0131 6)50 5776
Email: A.Teckentrup@ed.ac.uk
Course secretaryMiss Sarah McDonald
Tel: (0131 6)50 5043
Email: sarah.a.mcdonald@ed.ac.uk
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