Cellular Neural Networks and Visual Computing
Autor Leon O. Chua, Tamas Roskaen Limba Engleză Paperback – 15 iun 2005
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Specificații
ISBN-13: 9780521018630
ISBN-10: 0521018633
Pagini: 412
Ilustrații: 50 tables 36 exercises
Dimensiuni: 170 x 244 x 22 mm
Greutate: 0.71 kg
Ediția:Revised
Editura: Cambridge University Press
Locul publicării:Cambridge, United Kingdom
ISBN-10: 0521018633
Pagini: 412
Ilustrații: 50 tables 36 exercises
Dimensiuni: 170 x 244 x 22 mm
Greutate: 0.71 kg
Ediția:Revised
Editura: Cambridge University Press
Locul publicării:Cambridge, United Kingdom
Cuprins
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).
Recenzii
"...rarely has a treatment of a new technology been so thoroughly researched and presented within the confines of a single book...an outstanding example of what a team of dedicated authors and a committed publisher can do towards exposing their potential readers to new technologies and development of new industries." Current Engineering Practice
Descriere
A unique undergraduate level textbook on Cellular Nonlinear/neural Networks (CNN) technology and analogic computing.