Distributed Signal Processing - A Confluence of Many Disciplines (source: https://www.astesj.com/v05/i04/p39)
Distributed acoustic signal processing, an emerging field that encompasses many disciplines, deals with the processing of audio signals either captured or to be reproduced by numerous distributed audio devices.
This course will provide a fundamental introduction to the theory and practice of distributed processing of acoustic signals.
Students will learn about the core concepts, benefits, and challenges of distributed acoustic signal processing. The course focuses primarily on applications using distributed microphones, e.g., for enhancing speech in a teleconference, source separation, or sound classification.
Students will gain experience in implementing and testing different algorithms for a network of distributed microphones. At the end of this course, students will understand the basics of distributed acoustic signal processing and can implement (in Python) a distributed sensing system, both conceptually and practically.
Eligibility: Students from TUM, University of Stuttgart, and FAU
Background: Electrical Engineering, Computer Science, Information and Communication Technology, Mathematics, Physics, Acoustics
Experience: Bachelor students from 4th semester and Master students