Leon O. Chua, Tamas Roska

Cellular Neural Networks and Visual Computing

Foundations and Applications

• Gebundenes Buch

Produktbeschreibung

Cellular Nonlinear/Neural Network (CNN) technology is both a revolutionary concept and an experimentally proven new computing paradigm. Analogic cellular computers based on CNNs are set to change the way analog signals are processed. This unique undergraduate level textbook includes many examples and exercises, including CNN simulator and development software accessible via the Internet. It is an ideal introduction to CNNs and analogic cellular computing for students, researchers and engineers from a wide range of disciplines. Leon Chua, co-inventor of the CNN, and Tamà s Roska are both highly respected pioneers in the field.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 410
• Erscheinungstermin: 12. Januar 2011
• Englisch
• Abmessung: 260mm x 183mm x 27mm
• Gewicht: 963g
• ISBN-13: 9780521652476
• ISBN-10: 0521652472
• Artikelnr.: 22081096

Inhaltsangabe

1. Once over lightly
2. Introduction - notations, 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
15. Visual microprocessors - analog and digital VLSI implementation of the CNN universal machine
16. CNN models in the visual pathway and the 'bionic eye'
Appendix A. A CNN template library
Appendix B. Using a simple multi-layer CNN analogic dynamic template and algorithm simulator (CANDY)
Appendix C. A program for binary CNN template design and optimization (TEMPO).