To give a deeper understanding on artificial and biological neural network systems.
1. Introduction
2. Neurophysiological Background
3. Biological Memories and Associative Memories
4. Supervised Learning Models
5. Back-Propagation for Inverse Problems
6. Unsupervised Learning and Self-Organization
7. Efficiency Evaluation of Neural Systems
8. Multi-Network Systems
9. Applications in Sociology, Mechanics and Medicine
10. Neuroethology and Network Realization
Original Prints in English
Report in English