Neural Networks A

LV-Nr: 708.073 VO, 708.074 UE
Course Homepage:
TUGonline link: Neural Networks A
Core course of the "Computational Intelligence" Catalog

Neural Networks are a technology which mimics certain aspects of biological mechanisms of computation and learning. They can be used as flexible solution for many practical problems, for example from areas such as pattern classification, optimization, control, and knowledge-based systems.

This course gives an introduction to computing and learning on artificial neural networks. The most commonly used algorithms for adaptive neural networks are investigated, and competing methods from artificial intelligence and statistics are discussed.

The presented topics include:

• The Perceptron Model
• Multilayer Perceptrons
• Backpropagation and Extensions
• Radial Basis Function Networks
• Unsupervised Learning (PCA, ICA)
• Kohonen Maps
• Hopfield Networks
• Echo State Networks
• Bayesian Techniques for Artificial Neural Networks