Detail publikace

Comparison of FPNNs Models Approximation Capabilities and FPGA Resources Utilization

KRČMA, M. KOTÁSEK, Z. LOJDA, J.

Originální název

Comparison of FPNNs Models Approximation Capabilities and FPGA Resources Utilization

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents the concepts of FPNA and FPNN, used for the approximation of artificial neural networks in FPGAs and introduces derived types of these concepts used by the authors. The process of transformation of a trained artificial neural network to an FPNN is  described. The diagram of the FPGA implementation is presented. The results of experiments determining the approximation capabilities of FPNNs are presented and the FPGA resources utilization are compared.

Klíčová slova

ANN, FPNN, FPGA

Autoři

KRČMA, M.; KOTÁSEK, Z.; LOJDA, J.

Vydáno

6. 9. 2017

Nakladatel

IEEE Computer Society

Místo

Cluj-Nappoca

ISBN

978-1-5386-3368-7

Kniha

Proceedings of IEEE 13th International Conference on Intelligent Computer Communication and Processing

Strany od

125

Strany do

132

Strany počet

8

URL

https://www.fit.vut.cz/research/publication/11507/

BibTex

@inproceedings{BUT146266,
  author="Martin {Krčma} and Zdeněk {Kotásek} and Jakub {Lojda}",
  title="Comparison of FPNNs Models Approximation Capabilities and FPGA Resources Utilization",
  booktitle="Proceedings of  IEEE 13th International Conference on Intelligent Computer Communication and Processing",
  year="2017",
  pages="125--132",
  publisher="IEEE Computer Society",
  address="Cluj-Nappoca",
  doi="10.1109/ICCP.2017.8116993",
  isbn="978-1-5386-3368-7",
  url="https://www.fit.vut.cz/research/publication/11507/"
}

Dokumenty

bare_conf.pdf