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Høst 2016
SMN6190 Linear Algebra 2 - 5 stp
The course is administrated by
Type of course
Course contents
Content
Particular and general vector spaces, subspaces, basis. Gram-Schmidt process, least-squares problems. Inner product spaces. Development of the theory of eigenvalues and eigenvectors. Diagonalization with generalizations. Singular value decompositions. Linear transformations with matrix representations.
Application deadline
Admission requirements
ADMISSION REQUIREMENTS: A relevant undergraduate bachelor Engineering programme with minimum 30 credits mathematics/statistics topics
Application code: 9371
Objective of the course
Learning outcomes, skills and attitudes
Knowledge about theory, facts, concepts and procedures in linear algebra, which constitute a fundamental basis for the professional disciplines.
Knowledge in how to solve theoretical and practical tasks by algebraic arguments. Emphasis on how to communicate results.
Knowledge in how to analyze sources of information and by logical reasoning in linear algebra derive solutions to problems.
Language of instruction
Teaching methods
Working and assessment methods
Lectures and task solution sessions. Video lectures.
Two distributed assignments to be completed.
Final, summative exam.
Assessment
Mandatory tasks
One mandatory questionnaire is to be submitted before the exam.
Assessement: 4 hour written exam accounting for the total grade in the course. Grading will be done by using A-F grading scale, F is Fail. A re-sit exam will be arranged for this course.
Date for examination
The date for the exam can be changed. The final date will be announced at your faculty early in May and early in November.
Recommended reading/syllabus
Curriculum
David Lay: Linear Algebra and Its Applications, latest edition.
Compendia: 'Linear systems, matrices and determinants', 'Real eigenvalues and eigenvectors'
Additional theory, texts and examples on It's learning.
Lecture notes. Web lectures.
Additional literature
G. Strang: Linear algebra and its applications
H. Anton: Elementary linear algebra
E. Kreyszig: Advanced engineering mathematics.