Signal Processing and Speech Communication Laboratory

Computational Intelligence Lectures

Course Scripts and Lecture Material

Part I (Anand, Guillaume)

06.03.2018
Lecture 1
20.03.2018
Lecture 2
10.04.2018
Lecture 3
17.04.2018
Lecture 4
24.04.2018
Lecture 5
02.05.2018
Lecture 6

Further reading material can be found under Bibliography.

2016 materials:

Part II (Pernkopf)

Script and course notes part 1, part2.

In addition, the slides of the HMMs and the tutorial + slides of the Graphical Models are important. From the tutorial Section 3, 4.1, 4.2, 5.1, 5.2, 5.4, and 7 (without sub-chapters) are relevant.

Course overview: Parametric & Non-Parametric Density Estimation

Bayes Classifier:

Gaussian Mixture Model & k-means:

Markov Model & Hidden Markov Model:

Graphical Models:

PCA & LDA: