Cellular neural networks and visual computing : foundation and applications
This is a unique undergraduate level textbook on Cellular Nonlinear/neural Networks (CNN) technology. The many examples and excercises, including a simulator accessible via the Internet, make this book an ideal introduction to CNNs and analogic cellular computing for students, researchers and engine...
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| Main Author | |
|---|---|
| Other Authors | |
| Format | Electronic eBook |
| Language | English |
| Published |
Cambridge, UK ; New York, NY :
Cambridge University Press,
2002.
|
| Subjects | |
| Online Access | Full text |
| ISBN | 1601197357 9781601197351 0511040512 9780511040511 9780511754494 0511754493 9780511048258 0511048254 0511157827 9780511157820 1280420677 9781280420672 9786610420674 661042067X 1107117461 9781107117464 0511176945 9780511176944 0511329849 9780511329845 9780521018630 0521018633 9780521652476 0521652472 |
| Physical Description | 1 online resource (xi, 396 pages) : illustrations |
Cover
Table of Contents:
- 1. Introduction
- 2. Notation, definitions, and mathematical foundation
- 3. Characteristics and analysis of simple CNN templates
- 4. Simulation of the CNN dynamics
- 5. Binary CNN characterization via Boolean functions
- 6. Uncoupled CNNs: unified theory and applications
- 7. Introduction to the CNN Universal Machine
- 8. Back to basics: Nonlinear dynamics and complete stability
- 9. The CNN Universal Machine (CNN-UM)
- 10. Template design tools
- 11. CNNs for linear image processing
- 12. Coupled CNN with linear synaptic weights
- 13. Uncoupled standard CNNs with nonlinear synaptic weights
- 14. Standard CNNs with delayed synaptic weights and motion analysis.