Computational Intelligence, SS08
2 VO 442.070 + 1 RU 708.070 last updated:
Course Notes (Skriptum)
Online Tutorials
Introduction to Matlab
Neural Network Toolbox
OCR with ANNs
Adaptive Filters
VC dimension
Gaussian Statistics
PCA, ICA, Blind Source Separation
Hidden Markov Models
Mixtures of Gaussians
Automatic Speech Recognition
Practical Course Slides
Animated Algorithms
Interactive Tests
Key Definitions
Literature and Links

Mixtures of Gaussians

A Tutorial for the Course Computational Intelligence


This tutorial treats mixtures of Gaussian probability distribution functions. Gaussian mixtures are combinations of a finite number of Gaussian distributions. They are used to model complex multi-dimensional distributions. When there is a need to learn the parameters of the Gaussian mixture, the EM algorithm is used. In the second part of this tutorial mixtures of Gaussian are used to model the emission probability distribution function in Hidden Markov Models.


To make full use of this tutorial you should
  1. Download the file which contains this tutorial in printable format (PDF and ps.gz) and the accompanying MATLAB programs.
  2. Unzip which will generate a subdirectory named MixtGaussian/matlab where you can find all the MATLAB programs.
  3. Add the folder MixtGaussian/matlab and the subfolders to the MATLAB search path with a command like addpath('C:\Work\MixtGaussian\matlab') if you are using a Windows machine or addpath('/home/jack/MixtGaussian/matlab') if you are using a Unix/Linux machine.