MAT-62006 Inverse Problems, 7 cr
Additional information
Suitable for postgraduate studies.
Person responsible
Sampsa Pursiainen, Mikko Kaasalainen
Lessons
| Implementation | Period | Person responsible | Requirements |
| MAT-62006 2018-01 | 4 |
Sampsa Pursiainen |
Evaluation: Exam, exercises and project work |
Learning Outcomes
Examples of inverse problems include applications of medical imaging and geophysical prospecting using electrical measurements, The related inverse problems are sensitive to measurement errors: straightforward inversion attempts lead to failure. Therefore spezialized solution methods are needed. This course gives an overview of classical and statistical solution methods for inverse problems. Both theory and computer implementation are discussed, and the methods are demonstrated with practical inverse problems involving measured data.
Content
| Content | Core content | Complementary knowledge | Specialist knowledge |
| 1. | Introduction to statistical (Bayesian) inversion. Theory and implementation of Monte Carlo Markov Chain methods. | ||
| 2. | Iterative regularization. | ||
| 3. | Practical applications of inverse problems |
Study material
| Type | Name | Author | ISBN | URL | Additional information | Examination material |
| Lecture slides | Käänteiset ongelmat | Jari Kaipio | No | |||
| Summary of lectures | Inverse problems course text | Sampsa Pursiainen | Yes | |||
| Online book | Inversio-ongelmat | Erkki Somersalo | No |
Prerequisites
| Course | Mandatory/Advisable | Description |
| MAT-60000 Matriisilaskenta | Mandatory | |
| MAT-60006 Matrix Algebra | Mandatory |
Correspondence of content
| Course | Corresponds course | Description |
| MAT-62006 Inverse Problems, 7 cr | MAT-52506 Inverse Problems, 6 cr | |
| MAT-62006 Inverse Problems, 7 cr | MAT-62007 Inverse Problems, 5 cr |