OUTLINE
1. Neural network concepts:
What is a neural network? Biological neuron, artificial neuron, topologies.
2. Learning in neural networks
Types of learning and learning rules: Error correction learning, Hebbian learning,
Competitive learning, Boltzmann learning.
3. Application tasks:
Functional approximation, classification, association, application examples.
4. Feedforward networks:
Perceptron, multi-layer perceptron, radial basis function network, self-organizing feature
map.
5. Feedback networks:
Hopfield, Boltzman machine, real-time recurrent network.