DocumentCode
2516803
Title
Design and learning with cellular neural networks
Author
Nossek, Josef A.
Author_Institution
Inst. for Network Theory & Circuit Design, Tech. Univ. Munchen, Germany
fYear
1994
fDate
18-21 Dec 1994
Firstpage
137
Lastpage
146
Abstract
The template coefficients (weights) of a CNN, which will give a desired performance, can either be found by design or by learning; “By design” means, that the desired function to be performed could be translated into a set of local dynamic rules, while “by learning” is based exclusively on pairs of input and corresponding output signals, the relationship of which may be by far too complicated for the explicit formulation of local rules. An overview of design and learning methods applicable to CNNs, which sometimes are not clearly distinguishable,is given here. Both technological constraints imposed by specific hardware implementation and practical constraints caused by the specific application and system embedding are influencing design and learning
Keywords
cellular neural nets; learning (artificial intelligence); cellular neural networks; learning; local dynamic rules; system embedding; technological constraints; template coefficients; Cellular neural networks; Circuit synthesis; Design methodology; Design optimization; Electronic mail; Equations; Hardware; Image processing; Linear feedback control systems; Signal design;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1994. CNNA-94., Proceedings of the Third IEEE International Workshop on
Conference_Location
Rome
Print_ISBN
0-7803-2070-0
Type
conf
DOI
10.1109/CNNA.1994.381694
Filename
381694
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