Hardware radial basis function neural network automatic generation


  • Lucas Leiva INCA/INTIA, UNCPBA, Tandil, 7000, Argentina
  • Nelson Acosta INCA/INTIA, UNCPBA, Tandil, 7000, Argentina


RBF Neural Networks, FPGA, Pattern recognition, Architecture


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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How to Cite

Leiva, L., & Acosta, N. (2011). Hardware radial basis function neural network automatic generation. Journal of Computer Science and Technology, 11(01), p. 15–20. Retrieved from https://journal.info.unlp.edu.ar/JCST/article/view/683



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