Cellular Neural Networks and Analog VLSI / Edition 1

by Leon Chua, Glenn Gulak, Edmund Pierzchala, ïngel Rodrïguez-Vïzquez

Overview

Cellular Neural Networks and Analog VLSI brings together in one place important contributions and up-to-date research results in this fast moving area.
Cellular Neural Networks and Analog VLSI serves as an excellent reference, providing insight into some of the most challenging research issues in the field.

Product Details

ISBN-13:	9780792381259
Publisher:	Springer US
Publication date:	02/28/1998
Edition description:	Reprinted from ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 15:3, 1998
Pages:	103
Product dimensions:	7.01(w) x 10.00(h) x 0.01(d)

Table of Contents

A 16 × 16 Cellular Neural Network Universal Chip: The First Complete Single-Chip Dynamic Computer Array with Distributed Memory and with Gray-Scale Input-Output.- A 6 × 6 Cells Interconnection-Oriented Programmable Chip for CNN.- Analog VLSI Design Constraints of Programmable Cellular Neural Networks.- Focal-Plane and Multiple Chip VLSI Approaches to CNNs.- Architecture and Design of 1-D Enhanced Cellular Neural Network Processors for Signal Detection.- Analog VLSI Circuits for Competitive Learning Networks.- Design of Neural Networks Based on Wave-Parallel Computing Technique.

Editorial Reviews

‘...anyone serious about CNNs should have this book on his or her bookshelf.'
International Journal of Electrical Engineering Education, April 2001

From the Publisher

Seven papers demonstrate recent results in the broad class of analog systems called "cellular neural networks" (CNNs), which consist of an array of locally-interacted analog circuit units, called "cells." The architecture, design, and implementation of a number of different CNN chips are examined in detail, and numerous schematic drawing are included throughout. A special issue of , v.15, no.3, 1998. Annotation c. by Book News, Inc., Portland, Or.

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