Approximate Outline of Topics
Introduction and Overview
Biological Background
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Large-scale organization of the brain
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Basic neurobiology of the neuron
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Lateral inhibition in animal nervous systems
History and Development of Neural Network Models
Review of Linear Algebra
Single-Layer Networks
- Linear associators
- Simple perceptrons
- Perceptron convergence theorem
- Gradient descent learning
- Delta rule
Multi-Layer Networks
- Multi-layer perceptrons
- Backpropagation
- Variations on backpropagation
Recurrent Networks
- Hopfield networks
- Boltzmann machines and simulated annealing
- Elman networks and sequence learning
- Brain-State-in-a-Box model
- Recurrent backpropagation
Unsupervised Networks
- Competitive learning
- Vector quantization
- Kohonen self-organizing maps
Sparse Distributed Memory
Distributed Representations of Information
- Recursive Auto-Associative Memory
- Holistic processing
- Finding structure in time
- Binary spatter coding
- Holographic Reduced Representations
Evolutionary Approaches
- Designing neural networks with genetic algorithms
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Evolutionary reinforcement learning