DocumentCode
1575243
Title
Capacity of cellular neural networks as associative memories
Author
Lukianiuk, Andrzej
Author_Institution
Inst. of Control & Ind. Electron., Warsaw Univ. of Technol., Poland
fYear
1996
Firstpage
37
Lastpage
40
Abstract
In the paper a cellular neural network (CNN) architecture as an associative memory is considered. The boundary for the maximum number of memory vectors is obtained. The result suggests that the maximum number of memory vectors arbitrarily chosen from a set of linearly independent vectors is not related to the size of CNN but depends only on radius of the neighborhood
Keywords
cellular neural nets; content-addressable storage; neural net architecture; associative memories; cellular neural networks; linearly independent vectors; memory vectors; Associative memory; Cellular neural networks; Design methodology; Equations; Hopfield neural networks; Industrial electronics; Memory architecture; Network synthesis; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on
Conference_Location
Seville
Print_ISBN
0-7803-3261-X
Type
conf
DOI
10.1109/CNNA.1996.566486
Filename
566486
Link To Document