Universität Wien

280390 VO Inverse Problems (2023W)

4.00 ECTS (3.00 SWS), SPL 28 - Erdwissenschaften, Meteorologie - Geophysik und

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Details

max. 20 participants
Language: English

Examination dates

Lecturers

Classes (iCal) - next class is marked with N

The course will start from 12th October

  • Thursday 05.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 12.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 19.10. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 09.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 16.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 23.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 30.11. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 07.12. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 14.12. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 11.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 18.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II
  • Thursday 25.01. 12:00 - 14:30 Seminarraum Paläontologie 2B311 3.OG UZA II

Information

Aims, contents and method of the course

The course deals with the resolution of ill-posed problems, e.g. inverse problems from physics and simple problems from data science of data fitting type. More precisely, the following aspects will be covered:
-- Linear regression (and statistical aspects of least squares)
-- Discretization of continuous inverse problems
-- Rank deficiency and ill-conditioning (the SVD and the generalized inverse)
-- Tikhonov regularization
-- Iterative methods (CG and CGLS methods)
-- Nonlinear regression (Newton's method etc).

All of these topics will be complemented with exercises (Matlab or Octave).

Assessment and permitted materials

Oral examination. Examination dates are by appointment.

Minimum requirements and assessment criteria

Knowledge of linear algebra and basic programming skills.
Participation in the course and project assignments.

Examination topics

General knowledge and understanding of the topics covered in the course.

Reading list

R.C. Aster, B. Borchers, C.H. Thurber: Parameter Estimation and Inverse Problems, Elsevier, 2013

Association in the course directory

MA PE 01

Last modified: We 06.03.2024 15:46