Signal Processing and Machine Learning

What it is about

You will learn advanced mathematical methods, concepts and algorithms from signal processing and machine learning and apply them. The focus is on the integration of both paradigms with applications in communication and data processing. In the end, you can reformulate typical problem statements, apply suitable algorithms (e.g., for sparse signal processing or neural networks) and evaluate their results.

What you will be able to do

• Understand mathematical concepts and numerical algorithms in signal processing and ML
• Apply and evaluate algorithms for communication and data processing tasks
• Formulate problem statements so that sparse-signal procedures and ML methods are applicable
• Gain insight into current research questions of the topics covered

What the module consists of

• LecturesIntroduction to concepts and algorithms and demonstration using applications
• Exercises / Case StudiesTransfer of lecture content to application examples and problem statements
• Programming Tasks / Practical WorkIndependent implementation of numerical algorithms and use of toolboxes

Teaching method

• LecturesIntroduction of mathematical concepts and algorithms
• Case Studies / ApplicationsDemonstration of the use of concepts in concrete examples
• Independent Tasks and ProgrammingDeepening through application and implementation of own as well as existing toolboxes