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Course MAT261

Numerical Linear Algebra

Course offered :

Current programmes of study

Course offered by

Number of credits 10
Course offered (semester) Autumn
Schedule Schedule
Reading list Reading list

Language of Instruction

English

Pre-requirements

None

Learning Outcomes

Upon completion of the course, the successful candidate shall be able to:

  • Choose the most appropriate numerical method to solve a given linear algebra problem.
  • Explain and describe the principles of SVD, QR, LU and Cholesky factorization of matrices.
  • Have the knowledge of different methods for eigenvalue problems, like power method, divide and conquer and QR method.
  • Explain the principles of Krylov subspace methods, like the Arnoldi iteration, GMRES, Lanczos iteration and conjugate gradients.
  • Analyze the speed and rate of convergence and stability of numerical algorithms.

Contact Information

advice@mi.uib.no

Course offered (semester)

Autumn

Language of Instruction

English

Aim and Content

This course deals with algorithms to solve: The eigenvalue problem superdeterminant equation systems and linear equation systems (onlyKrylov subspace iteration). Algorithms for matrix decomposition as QR-factorisation and Singular-value decomposition will be discussed and analysed with respect to stability and complexity.

Learning Outcomes

Upon completion of the course, the successful candidate shall be able to:

  • Choose the most appropriate numerical method to solve a given linear algebra problem.
  • Explain and describe the principles of SVD, QR, LU and Cholesky factorization of matrices.
  • Have the knowledge of different methods for eigenvalue problems, like power method, divide and conquer and QR method.
  • Explain the principles of Krylov subspace methods, like the Arnoldi iteration, GMRES, Lanczos iteration and conjugate gradients.
  • Analyze the speed and rate of convergence and stability of numerical algorithms.

Pre-requirements

None

Recommended previous knowledge

MAT160 Scientific computing I

Compulsory Requirements

Exercises.

Assessment methods

Written exam. It is opportunity for grades on exercises, which can be included in the final grade. If less than 20 students are taking the course, it can be oral exam.

Grading Scale

The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.

Contact Information

advice@mi.uib.no