After successful completion of the course, students are able to, carry out a study of literature concerning a complex mathematical question, to work out the work the results of the study, provide a lecture and discuss the results with the participants of the seminar. The seminar work will be documented in writing.

compressive sensing comprises a variety of methods and mathematical techniques to determine parameters of a model from (measured) data. Typical applications include medical imaging, radar measurements, and mobile communication. The practically relevant case is that where the number of measurements is not sufficient to determine the parameters uniquely. In this case, the additional assumption of "sparsity" comes in, i.e., the assumption that the sought parameter vector has only view non-zero entries. Under such an assumption, the problem can be formulated in meaningful way and solved. The goal of the seminar is to present algorithms that are commonly used in compressive sensing. The seminar will be based on the book by Foucart and Rauhut.

Supervised discussion of a selected topic  with the help of mathematical literature (books, scientific papers), presentation by students with feedback, supervision for scientific writing in Latex.

first meeting: TUE, October 12, 2021 at 12:00 at https://tuwien.zoom.us/j/92522094590?pwd=d3FZRjNJYzcxTXcvZE1ocHdyVDVEdz09

The grade consists of the presentation and the written seminar paper in approximately equal parts,