
Cellular Neural Networks and Analog VLSI
Kluwer Academic Publishers
Published on 28. February 1998
Book
Hardback
IV, 103 pages
978-0-7923-8125-9 (ISBN)
Description
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.
Cellular Neural Networks and Analog VLSI serves as an excellent reference, providing insight into some of the most challenging research issues in the field.
Reviews / Votes
` ...anyone serious about CNNs should have this book on his or her bookshelf. 'International Journal of Electrical Engineering Education, April 2001
More details
Edition
Reprinted from ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING, 15:3, 1998
Language
English
Place of publication
New York
United States
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Illustrations
70 s/w Abbildungen, 1 farbige Abbildung
IV, 103 p. 71 illus., 1 illus. in color.
Dimensions
Height: 260 mm
Width: 183 mm
Thickness: 12 mm
Weight
441 gr
ISBN-13
978-0-7923-8125-9 (9780792381259)
DOI
10.1007/978-1-4757-4730-0
Schweitzer Classification
Other editions
Additional editions

Leon Chua | Glenn Gulak | Edmund Pierzchala
Cellular Neural Networks and Analog VLSI
E-Book
03/2013
Springer
€96.29
Available for download

Leon Chua | Glenn Gulak | Edmund Pierzchala
Cellular Neural Networks and Analog VLSI
Book
12/2010
Springer
€106.99
Shipment within 15-20 days
Content
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.