Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence

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Mathematical Signal and Image Processing

Course Description

Images are the maybe most prominent type of data processed nowadays. What might be less known is that signal and image processing has a rich mathematical history. Initiated decades ago, mathematical signal and image processing has been examining methods for the acquisition and analysis of audio and video signals. In light of modern data science the therein developed theory reveals the intrinsic structure of such data, and allows compression and recovery from (seemingly) underdetermined measurements.

This lecture will provide an introduction into this exciting research area, which is today a fundamental part of mathematical data science and machine learning. The topics we discuss will encompass:

  • Compressed Sensing
  • Frame Theory
  • Wavelet Theory

Schedule and Venue

  • Lecture: Tue and Thu, 10.00-12.00 Uhr (Room B 251)
  • Exercise Class: Wed, 10.00-12.00 (Room B 039)
  • Tutorial: Tue, 16.00-18.00 (Room B 040)
  • Office Hours: Thu 15.30-16.30 (Room 514 in Akademiestr. 7) and Wed 14.00-15.00 (Room 510 in Akademiestr. 7); please write a short e-mail that you plan to come.
  • Exam: February 16, 2023, 10.00-12.00


The course is targeted at Master students from mathematics. The course requires knowledge of the topics from the course “Maßtheorie und Integralrechnung mehrerer Variablen”. Moreover, basic knowledge of functional analysis is highly recommended.

Creditable Modules

- Master in Mathematics: WP35 Fortgeschrittene Themen aus der künstlichen Intelligenz und Data Science (9 ECTS)
- Master in Financial and Insurance Mathematics: WP13 Advanced Topics in Mathematics A (9 ECTS)


Please register for our course on uni2work (access key: MSIP2022).