Instructions Term Project (Final)

Course Neural Network Types

1. Data Separation in N-Dimensions

 - Hyperplane Separation
 - Nonlinear Separation  
 - Perceptrons
 - Supervised Learning
 - Unsupervised/Self-Organizing Learning
 - Clustering (self-organizing)
 - An Example: the Radial Basis Function NN (supervised learning)
 - RBFNN Derivation
 - RBFNN Algorithm

2. Neural Network Basics

 - backpropagation NNs
 - BP Architecture and Derivation
 - BP Algorithm
 - Radial Basis Functional Link Nets (NN)
 - RBFLN Tutorial
 - Momentum for Efficient Weight Training

3. Related Neural Networks

 - Probabilistic Neural Networks
 - Probablistic NN Tutorial
 - Fuzzy Set Membership Functions
 - A FNN Tutorial
 - A Simple (Nearest Neighbor) Fuzzy NN
 - A BP Fuzzy Neural Network
 - Robot Obstacle Avoidance FNN
 - A Learning FNN

4. Other Types of Neural Networks

 - Unsupervised Competitive Learning Networks
 - Park's Centroid UCL paper
 - Hopfield Recurrent NNs
 - Support Vector Machines

5. Data and Project Ideas

 - The UC Irvine Repository of Machine Learning Databases
 - UC Irvine Repository
 - Link to Data Sets
 - Support Vector Machine Project Ideas
 - Some Project Ideas for Hopfield NNs
 - Project Idea for Improved UCL

6. Application Papers

 - Application Data Notes
 - Paper on Association Rule Mining
 - Paper on Association Rule Classifier
 - Paper on NN with K-Means Clustering
 - Paper on Fuzzy RBF NN for EKG
 - Paper on Self-Organizing Map and K-Means
 - NN for Egg Defect Detection
 - NN for Medical Diagnosis
 - NN for Data Fusion
 - Fuz. Competitive Learning of NNMRI Scans
 - NN for Power Forecasting
 - NN for Thyroid Diagnosis
 - NN Unsupervised Learning and Principal Component Analysis
 - Sorting Rules in Associative Classification
 - Generating Rules from Examples
 - SVM Paper for Medical Imaging
 - SVM Ocean Chlorophyll Application
 - SVM Speech Recognition
 - Kernel Based Clustering

7. Other Special Techniques

 - Feature Voting
 - K-means Clustering
 - Kernel Methods