This book presents a comprehensive description of the emerging technology of cellular neural networks (CNNs), the first general purpose analog microprocessors with applications including real-time image and audio processing, image recognition, and the solution of partial differential equations. It discusses some realistic industrial applications of CNNs (including automatic fruit classification, nuclear magnetic resonance spectra image processing, environmental modeling and simulation for pollution distribution forecast). Particular attention is paid to the study of CNNs in the context of nonlinear circuit theory. Emphasis is also given to chaotic oscillators and their application in secure communication and spread-spectrum systems. Discussed in addition is the subject of spatio-temporal dynamic phenomena in two-dimensional CNNs. It is shown how traveling wavefronts, spirals, and Turing patterns can develop in a regular and topologically simple array. The book is completed by the description of a real CMOS discrete-time switched-current chip implementation of a CNN. The book offers thorough discussions that range from issues at the system-level, which are characterized by a rigorous analytic approach, to the technological and IC design aspects. Examples, simulation studies and experimental results complement the theoretical results throughout.

This book covers the whole spectrum of cellular neural networks. Examples, simulation results, and experimental results are complemented by theoretical discussions throughout the whole book. Includes supplementary material: sn.pub/extras

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