Adaptive Filters

Lecture Notes

Lecture number Date Topics Lecture notes
1 11.04.2016
  • Introduction
  • Boundary conditions of the lecture
  • Motivation for adaptive filtering with audio application examples
Notes for all lectures on moodle.

2 18.04.2016
  • Signal properties
  • Signal models
  • Cost functions
 
3 25.04.2016
  • Wiener filter
  • Principle of orthogonality
 
4 02.05.2016
  • Linear prediction
    • Yule-Walker equations
    • Levinson-Durbin recursion
 
5 09.05.2016
  • Application of linear prediction
    • Redundancy reduction
    • Spectral envelope estimation
    • Parametric spectral estimation
 
6 23.05.2016
  • Adaptive filters (part 1 of 3)
    • Introduction
    • RLS algorithm
 
7 30.05.2016
  • Adaptive filters (part 2 of 3)
    • LMS algorithm
    • NLMS algorithm
 
8 06.06.2016
  • Adaptive filters (part 3 of 3)
    • Filtered x-LMS algorithm
    • Affine projection (AF) algorithm
 
9 13.06.2016
  • Filter design and control of adaptive filters
    • System distance
    • Optimum control parameters
 
10 20.06.2016
  • Kalman filters
 
11 27.06.2016
  • Kalman applications & Particle filters
 
12 04.07.2016
  • Processing structures
    • Frequency domain adaptive filtering
    • Filterbank structures
 
13 11.07.2016
  • Applications