Chua L.O., Roska T. Cellular Neural Networks and Visual Computing. Foundation and Applications

Издательство Cambridge University Press, 2004, -410 pp.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 Tamàs Roska are both highly respected pioneers in the field.Notation, definitions, and mathematical foundation
Characteristics and analysis of simple CNN templates
Simulation of the CNN dynamics
Binary CNN characterization via Boolean functions
Uncoupled CNNs: unified theory and applications
Introduction to the CNN Universal Machine
Back to basics: Nonlinear dynamics and complete stability
The CNN Universal Machine (CNN-UM)
Template design tools
CNNs for linear image processing
Coupled CNN with linear synaptic weights
Uncoupled standard CNNs with nonlinear synaptic weights
Standard CNNs with delayed synaptic weights and motion analysis
Visual microprocessors – analog and digital VLSI implementation of the CNN Universal Machine
CNN models in the visual pathway and the ‘‘Bionic Eye