Third-Cycle Courses

Faculty of Engineering | Lund University

Details for Course FMNN02F Introduction to Numerical Linear Algebra

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  • FMNN02F
  • Discontinued
Course Name
  • Introduction to Numerical Linear Algebra
Course Extent
  • 7.5
Type of Instruction
  • Course given jointly for second and third cycle
Administrative Information
  • 7154 (Centre of Mathematical Sciences / Numerical Analysis)
  • 2019-09-12
  • Professor Thomas Johansson

Current Established Course Syllabus

  • The aim of the course is to make the postgraduate student familiar with concepts and methods from numerical linear algebra. In general there are ready-made program libraries available but it is important to be able to recognize types of input which may cause problems for the most common methods.
  • Norms.
    Singular value decomposition and numerical rank.
    QR factorization, the Gram-Schmidt process and Householder matrices.
    Least squares problems and pseudoinverses.
    Linear systems of equations and condition numbers.
    Positive definite matrices and Cholesky factorization.
    Numeric determination of eigenvalues.
Knowledge and Understanding
  • For a passing grade the doctoral student must
  • be able to explain the concept of matrix norm

    be able to account for how one finds the singular value decomposition of a matrix, and to give examples of applications of the decomposition.

    be able to define the condition number of a matrix and to explain its relevance for the solution of systems of linear equations

    be able to describe common methods to numerically determine eigenvalues.
Competences and Skills
  • For a passing grade the doctoral student must
  • be able to implement given algorithms from numerical linear algebra in computer programs and use them to solve problems.

    be able to, in a well-structured report, account for the solution to a problem within the scope of the course.

Judgement and Approach
  • For a passing grade the doctoral student must
Types of Instruction
  • Lectures
  • Project
Examination Formats
  • Oral exam
  • Written assignments
  • Weekly hand-in assignments.
  • Failed, pass
Admission Requirements
Assumed Prior Knowledge
  • Calculus in several variables. Linear algebra including eigenvalues/vectors. Programming in Matlab or Python.
Selection Criteria
  • Trefethen, Lloyd N. & David Bau, I.: Numerical Linear Algebra. SIAM, 1997. ISBN 9780898713619.
Further Information
Course code
  • FMNN02F
Administrative Information
  • 2019-09-12
  • Professor Thomas Johansson

All Established Course Syllabi

1 course syllabus.

Valid from First hand in Second hand in Established
Autumn 2019 2019‑05‑20 18:30:08 2019‑06‑10 08:46:04 2019‑09‑12

Current or Upcoming Published Course Occasion

No matching course occasion was found.

All Published Course Occasions

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