NNGen: a powerful tool for the implementation of Artificial Neural Networks on a chip

Autores/as

  • Marcelo Tosini Universidad Nacional del Centro de la provincia de Buenos Aires, Argentina
  • Gerardo Acosta Universidad Nacional del Centro de la provincia de Buenos Aires, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

Palabras clave:

Data Mining, Machine Learning, Rule Learning, Exception

Resumen

A design and development tool to achieve artificial neural networks (ANN) implemented in a Field Programmable Gate Array (FPGA), is presented in this article. Its main components and functionality are thoroughly described. This tool, called NNGen, allows constructing digital ANN, which are easily programmable selecting different parameters. The output of such programming task is directly VHDL code to be ported to, in principle, any chip of the mentioned kind. A case study of a multilayer perceptron applied to weather forecast that was fully designed with NNGen, is also analyzed to obtain some conclusions.

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Publicado

2004-08-03

Cómo citar

Tosini, M., & Acosta, G. (2004). NNGen: a powerful tool for the implementation of Artificial Neural Networks on a chip. SADIO Electronic Journal of Informatics and Operations Research, 6, 42-52. https://revistas.unlp.edu.ar/ejs/article/view/17528