Pattern Recognition 2003:

Honours Course

**Introduction** (Please read!)

**Assignments:**

Your first task is to compile the latex source for Assignment 1. Use the latex command to compile it into a dvi file, which you can view using xdvi. Then use dvips or dvipdf to create a ps or pdf file respectively. If your operating system cannot do this, install one that can. This assignment is already due in week 1, so it's time to start having fun right away!

Assignment 1: Getting started

Assignment 2: K nearest neighbours classifier

Assignment 3: Optimal Bayes classifier

Assignment 4: Parametric Gaussian classifier

Assignment 5: Gaussian mixture model

Assignment 6: Principal component analysis

Assignment 7: Linear discriminant analysis

**Resources:**

**Theory:** Jain, Alder.
More lecture notes: Gaussians, Gaussian mixture models, PCA/LDA.

**LaTeX guide:** A not very short introduction to LaTeX

**BibTeX guide:** BIBTeXing (BibTeX is for bibliographies: you won't use it for this course, but if you become a LaTeX user you will find it useful later.)

**Matlab and Octave:** Matlab primer Octave homepage

**Code and data:**

Toy data sets for various experiments

Code fragment for KNN implementation

Data for speaker recognition experiments

Implementation of Gaussian mixture models

Synthetic data for PCA experiment 1

Synthetic data for PCA experiment 2

Facial expression recognition experiment

IO functions for facial expression data

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