DocumentCode
440451
Title
On cellular neural network learning
Author
Vilasís-Cardona, Xavier ; Vinvoles-Serra, M.
Author_Institution
Departamcnt d´´Electronica, Enginyeria i Arquitectura La Salle, Univ. Ramon Llull, Barcelona, Spain
Volume
1
fYear
2005
fDate
28 Aug.-2 Sept. 2005
Abstract
We study the continuous time two neuron CNN in the context of a supervised learning problem and extract the convergence map for constant inputs. From this result we can design a CNN cloning template for a classification problem. Some of the parameters of this cloning template play no effective role in the tesselation giving the convergence map. This gives some hints on how to set up a learning problem and solves the template composition problem for this case.
Keywords
cellular neural nets; learning (artificial intelligence); cellular neural network learning; classification problem; cloning template; continuous time CNN; convergence map; supervised learning problem; template composition problem; tesselation; Cellular neural networks; Cloning; Convergence; Cost function; Input variables; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuit Theory and Design, 2005. Proceedings of the 2005 European Conference on
Print_ISBN
0-7803-9066-0
Type
conf
DOI
10.1109/ECCTD.2005.1522933
Filename
1522933
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