A/Prof. Andrew P. Paplinski

CSE5301 Neural Networks and Fuzzy Systems
(Neuro-Fuzzy Computing)

Exam: Friday, June 3rd, 3-5pm. Venue: 11/H7

In order to use the lab after hours you need to go to the Faculty's homepage: http://www.infotech.monash.edu.au/ and click on "Request an IT or web service" to register for after hours access.

Assignments/Practicals

Assignment/practical 1

1. Introduction to MATLAB.
2. Basic properties of neural networks.
3. Perceptron.

Assignment/practical 2: Adaline and Multilayer Perceptron
Updated: 23 April 2005

1. Neural Network Toolbox.
   MATLAB demo script: fap2dLM.m
2. Linear Networks — Adaline and its applications.
3. Multilayer Perceptron — Back-Propagation.
4. Image coding algorithm
   MATLAB utilities: blkM2vc.m, vc2blkM.m,

Assignment/practical 3: Usupervised Learning
Version: 5 May 2005

1. Hebbian learning.
   MATLAB demo script: OjaPCA.m
2. Competitive learning.
3. Self-Organizing Maps.
   Related MATLAB scripts: FM22.m ,    sofm.m .

Assignment/practical 4: Fuzzy Inference Systems.

An extract from the Fuzzy Toolbox User's Guide (95 pages) can be found here fuzzyTut4.pdf

Lecture Notes

Table of contents

1. Lecture 1: Basic concepts of Neural Networks and Fuzzy Logic Systems

2. Lecture 2: Perceptron
   MATLAB demo script: perc.m

3. Lecture 3: ADALINE -- The Adaptive Linear Element
   MATLAB demo scripts: adln1.m ,    adlpr.m ,    adsid.m ,    adlnc.m ,    cJ2x.m

4. Lecture 4 (old version): Feedforward Multilayer Neural Networks -- part I
   Lecture 4 (improved version):
   MATLAB demo scripts: fap2Di.m ,    fap2D.m

5. Lecture 5: Feedforward Multilayer Neural Networks -- part II
   MATLAB demo scripts: nwini.m ,

6. Lecture 6: Unsupervised Learning (version: 28 Apr 05)
   Related MATLAB scripts: CmpInit.m, CmpLrn.m
   Self-Organizing maps: SOMs

7. Lecture 7 - Foundations of Fuzzy Logic
   L11fz pdf
   

8. Lecture 8 - Adaptive Neuro-Fuzzy Inference System
   L12fz pdf
   

2004 examination questions