Mathematics for Signals, Images and Structured Data

Signal and image processing is a discipline at the interface of several major scientific fields. In particular, mathematics plays a key role in understanding and modeling problems, and developing the algorithms for solving them. Initially, deeply associated with analysis, statistics and probability theory, mathematical approaches to signal processing involve increasingly diverse areas of mathematics, in response to the emergence of new issues and new types of data. The goal of this thematic month is to review the latest advances in mathematics for signal and image processing, their emergence and impact on several application fields (physics, biology, bio-medical, etc.)It will start with a research doctoral school on "Machine learning and signal processing". The following four weeks will focus successively on these themes: biomedical signals and images, statistical processing of structured data, audio and music signal processing, adaptive and multi-scale representations and their applications to large scale data, modeling and numerical simulation.​