Synergetic Computers and Cognition A Top-Down Approach to Neural Nets
This book presents a novel approach to neural nets and thus offers a genuine alternative to the hitherto known neuro-computers. This approach is based on the author's discovery of the profound analogy between pattern recognition and pattern formation in open systems far from equilibrium. Thus t...
| Main Author: | |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Berlin, Heidelberg
Springer Berlin Heidelberg
2004, 2004
|
| Edition: | 2nd ed. 2004 |
| Series: | Springer Series in Synergetics
|
| Subjects: | |
| Online Access: | |
| Collection: | Springer Book Archives -2004 - Collection details see MPG.ReNa |
Table of Contents:
- 1. Goal
- 2. What Are Patterns?
- 3. Associative Memory
- 4. Synergetics — An Outline
- 5. The Standard Model of Synergetics for Pattern Recognition
- 6. Examples: Recognition of Faces and of City Maps
- 7. Possible Realizations by Networks
- 8. Simultaneous Invariance with Respect to Translation, Rotation and Scaling
- 9. Recognition of Complex Scenes. Scene-Selective Attention
- 10. Learning Algorithms
- 11. Learning of Processes and Associative Action
- 12. Comparisons Between Human Perception and Machine “Perception”
- 13. Oscillations in the Perception of Ambiguous Patterns
- 14. Dynamic Pattern Recognition of Coordinated Biological Motion
- 15. Realization of the Logical Operation XOR by a Synergetic Computer
- 16. Towards the Neural Level
- 17. Concluding Remarks and Outlook
- Bibliography and Comments