Raster cellular neural network simulator for image processing applications with numerical integration algorithms

In this paper, a universal simulator for cellular neural network (CNN) is presented. This simulator is capable of performing Raster simulation for any size of input image, and thus is a powerful tool for researchers investigating potential applications of CNN. This paper reports the latency properti...

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Vydané v:International journal of computer mathematics Ročník 86; číslo 7; s. 1215 - 1221
Hlavný autor: Murugesh, V.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Abingdon Taylor & Francis 01.07.2009
Taylor & Francis Ltd
Predmet:
Algorithms
cellular neural networks
Euler algorithm
G.1.7
Image processing systems
Neural networks
Numerical analysis
ordinary differential equations
RK-Butcher algorithm
RK-Gill algorithm
Simulators
ISSN:0020-7160, 1029-0265
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Shrnutí:In this paper, a universal simulator for cellular neural network (CNN) is presented. This simulator is capable of performing Raster simulation for any size of input image, and thus is a powerful tool for researchers investigating potential applications of CNN. This paper reports the latency properties of CNNs along with popular numerical integration algorithms; results and comparisons are also presented.
Bibliografia:SourceType-Scholarly Journals-1
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ISSN:0020-7160
1029-0265
DOI:10.1080/00207160701798772