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...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2011-04-01
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| Series: | Journal of Computer Science and Technology |
| Subjects: | |
| Online Access: | https://journal.info.unlp.edu.ar/JCST/article/view/683 |
| Summary: | 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. |
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| ISSN: | 1666-6046 1666-6038 |