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MAT-52506 Inverse Problems, 6 cr |
Samuli Siltanen
Lecture times and places | Target group recommended to | |
Implementation 1 |
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3.-n. vuosikurssi
Biotekniikan koulutusohjelma DI-Opiskelijat Jatko-opiskelijat Luonnontieteiden ja ympäristötekniikan tiedekunta Sähkötekniikan koulutusohjelma Teknis-luonnontieteellinen koulutusohjelma Tietotekniikan koulutusohjelma |
Passed exam, sufficient activity in exercises, accepted project work.
Completion parts must belong to the same implementation
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Examples of inverse problems include medical imaging (CT, MRI), underground prospecting for ores using electrical measurements, recovering the shape of an asteroid from lightcurve observations, and sharpening a blurred photograph. These 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 modern 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 | Core content | Complementary knowledge | Specialist knowledge |
1. | Singular value decomposition of a matrix and solution by SVD truncation. Classical and generalized Tikhonov regularization. | ||
2. | Total variation regularization with emphasis on implementation issues. | ||
3. | Regularization using truncated iterative solvers. | ||
4. | Introduction to statistical (Bayesian) inversion. Theory and implementation of Monte Carlo Markov Chain methods. | ||
5. | Practical applications to medical imaging and signal processing. Emphasis on realistic large-scale problems. |
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Lecture slides | Inverse Problems | Fox, Nicholls, Tan | English | ||||
Lecture slides | Inverse Problems | Samuli Siltanen | English | ||||
Lecture slides | Käänteiset ongelmat | Jari Kaipio | Suomi | ||||
Online book | Inversio-ongelmat | Erkki Somersalo | Suomi |
Course | O/R |
MAT-31096 Matrix Algebra 1 | Recommended |
Course | Corresponds course | Description |
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Description | Methods of instruction | Implementation | |
Implementation 1 | Teaching in Period 1 consists of lectures and computer exercises. In period 2 the students complete a Matlab project work in small groups (1-3 persons). | Lectures Excercises Practical works |
Contact teaching: 0 % Distance learning: 0 % Self-directed learning: 0 % |