DocumentCode
921388
Title
The CNN paradigm
Author
Chua, Leon O. ; Roska, Tamás
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Volume
40
Issue
3
fYear
1993
fDate
3/1/1993 12:00:00 AM
Firstpage
147
Lastpage
156
Abstract
A concise tutorial description of the cellular neural network (CNN) paradigm is given, along with a precise taxonomy. The CNN is defined, and the canonical equations are described. The importance of many independent input signal arrays, adaptive templates, and the multilayer capability is emphasized and motivated by examples. It is shown how simply a wave-type partial differential equation can be generated
Keywords
neural nets; partial differential equations; CNN paradigm; adaptive templates; canonical equations; cellular neural network; input signal arrays; multilayer capability; taxonomy; wave-type partial differential equation; Analog computers; Biological system modeling; Cellular neural networks; Circuits; Computer networks; Grid computing; Laboratories; Signal processing; Solid modeling; Taxonomy;
fLanguage
English
Journal_Title
Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on
Publisher
ieee
ISSN
1057-7122
Type
jour
DOI
10.1109/81.222795
Filename
222795
Link To Document