Imaging in astronomy, geology and medicine require intelligent algorithms in order to obtain high fidelity images from noisy, incomplete data. The lecture will introduce into information theory and show how this can be used to construct statistical inference methods for such signal reconstruction problems.
topics will be addressed:
Aristotelian logic, Bayesian logic, measurement process (signal, response, noise), noise statistics (Gaussian, Poissonian), information measures (entropy, cross-information, ...), information Hamiltonian, relation to thermodynamics and statistical mechanics, theory of Wiener filter, construction of optimal non-linear filters, information field theory
Lecture notes + extra notes + more extra notes (to Sec. II.3) (handwritten, with typos, & errors, will be modified during lecturing)
Exercise sheets: No. 1, No. 2, No. 3, No. 4, No. 5, No. 6, No. 7 No. 8 No. 9,
The exam is scheduled for Friday, 2014-07-04 from 10am to 12pm in room B 134. In the tutorial session on Wednesday, 2014-07-02 and Thursday, 2014-07-03 instead of discussing a new exercise sheet, there will be a question and repetition session.
Previous examinations: Examination 2013, Examination 2012 (yes 2012, despite different date information in the document) , Examination 2011