Hardware radial basis function neural network automatic generation

This paper presents a parallel architecture for a radial basis function (RBF) neural network used for pattern recognition. This architecture allows defining sub-networks which can be activated sequentially. It can be used as a fruitful classification mechanism in many application fields. Several imp...

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Main Authors:	Lucas Leiva, Nelson Acosta
Format:	Article
Language:	English
Published:	Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata 2011-04-01
Series:	Journal of Computer Science and Technology
Subjects:	rbf neural networks fpga pattern recognition architecture
Online Access:	https://journal.info.unlp.edu.ar/JCST/article/view/683

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spelling	doaj-8ba9500abade49ff958a1a352c5f30da2021-05-05T13:52:01ZengPostgraduate Office, School of Computer Science, Universidad Nacional de La PlataJournal of Computer Science and Technology1666-60461666-60382011-04-0111011520378Hardware radial basis function neural network automatic generationLucas Leiva0Nelson Acosta1INCA/INTIA, UNCPBA, Tandil, 7000, ArgentinaINCA/INTIA, UNCPBA, Tandil, 7000, ArgentinaThis paper presents a parallel architecture for a radial basis function (RBF) neural network used for pattern recognition. This architecture allows defining sub-networks which can be activated sequentially. It can be used as a fruitful classification mechanism in many application fields. Several implementations of the network on a Xilinx FPGA Virtex 4-(xc4vsx25) are presented, with speed and area evaluation metrics. Some network improvements have been achieved by segmenting the critical path. The results expressed in terms of speed and area are satisfactory and have been applied to pattern recognition problems.https://journal.info.unlp.edu.ar/JCST/article/view/683rbf neural networksfpgapattern recognitionarchitecture
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Lucas Leiva Nelson Acosta
spellingShingle	Lucas Leiva Nelson Acosta Hardware radial basis function neural network automatic generation Journal of Computer Science and Technology rbf neural networks fpga pattern recognition architecture
author_facet	Lucas Leiva Nelson Acosta
author_sort	Lucas Leiva
title	Hardware radial basis function neural network automatic generation
title_short	Hardware radial basis function neural network automatic generation
title_full	Hardware radial basis function neural network automatic generation
title_fullStr	Hardware radial basis function neural network automatic generation
title_full_unstemmed	Hardware radial basis function neural network automatic generation
title_sort	hardware radial basis function neural network automatic generation
publisher	Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
series	Journal of Computer Science and Technology
issn	1666-6046 1666-6038
publishDate	2011-04-01
description	This paper presents a parallel architecture for a radial basis function (RBF) neural network used for pattern recognition. This architecture allows defining sub-networks which can be activated sequentially. It can be used as a fruitful classification mechanism in many application fields. Several implementations of the network on a Xilinx FPGA Virtex 4-(xc4vsx25) are presented, with speed and area evaluation metrics. Some network improvements have been achieved by segmenting the critical path. The results expressed in terms of speed and area are satisfactory and have been applied to pattern recognition problems.
topic	rbf neural networks fpga pattern recognition architecture
url	https://journal.info.unlp.edu.ar/JCST/article/view/683
work_keys_str_mv	AT lucasleiva hardwareradialbasisfunctionneuralnetworkautomaticgeneration AT nelsonacosta hardwareradialbasisfunctionneuralnetworkautomaticgeneration
_version_	1721460613978259456

Hardware radial basis function neural network automatic generation

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