Advanced Topics in Statistical Signal Processing

This course extends the signal processing fundamentals taught in DSP toward advanced topics that are the subject of current research. It is aimed at those with an interest in signal processing and a desire to extend their knowledge of signal processing theory in preparation for future project work, e.g., Master thesis, and their working careers.

Announcements

  • Due to the COVID-pandemic, the course will be a lecture instead of a seminar in this semester.
  • The lectures will be held live via Zoom.
  • There will be short group presentations of selected topics during the semester.
  • Only in the winter semester 2020/21 and upon successful completion, students can include this course either as a seminar or a lecture into their curriculum.
  • Note that these changes are temporary and only apply to the winter semester 2020/21

Course Overview

Title Advanced Topics in Statistical Signal Processing
Prerequisites DSP, general interest in signal processing, basic MATLAB knowledge
Format Lecture
Assessment Group presentations and final exam
Time/Room Mondays, 1.30-4.05 p.m. live via Zoom
First Meeting:
Oct 25, 2021, 1.30 p.m.
  • H. Krim & M. Viberg: Two decades of array signal processing research: the parametric approach, IEEE Signal Processing Magazine, 1996, 13, 67-94
  • A. Zoubir, V. Koivunen, Y. Chakhchoukh & M.Muma: Robust Estimation in Signal Processing: A Tutorial-Style Treatment of Fundamental Concepts, IEEE Signal Processing Magazine, 2012, 29, 61-80
  • A. Zoubir & D.Iskander: Bootstrap Methods in Signal Processing [From the Guest Editors], IEEE Signal Processing Magazine, 2007, 24, 7-8
  • A. Zoubir & D. Iskander: Bootstrap Methods and Applications, IEEE Signal Processing Magazine, 2007, 24, 10-19