Publication result detail

Mapping trained neural networks to FPNNs

KRČMA, M.; KAŠTIL, J.; KOTÁSEK, Z.

Original Title

Mapping trained neural networks to FPNNs

English Title

Mapping trained neural networks to FPNNs

Type

Paper in proceedings (conference paper)

Original Abstract

This paper introduces a set of methods for mapping
the trained neural networks into the lighted grid structured
Field Programmable Neural Networks without the use of a
training data set. These methods use information obtained from
original neural networks such as a network structure, connection
weights and biases. The principles of these mapping methods are
described and the used grid FPNNs are explained. The results of
experiments are presented and summarized.

English abstract

This paper introduces a set of methods for mapping
the trained neural networks into the lighted grid structured
Field Programmable Neural Networks without the use of a
training data set. These methods use information obtained from
original neural networks such as a network structure, connection
weights and biases. The principles of these mapping methods are
described and the used grid FPNNs are explained. The results of
experiments are presented and summarized.

Keywords

FPNA, FPNN, Artificial neural networks, FPGA

Key words in English

FPNA, FPNN, Artificial neural networks, FPGA

Authors

KRČMA, M.; KAŠTIL, J.; KOTÁSEK, Z.

RIV year

2016

Released

22.04.2015

Publisher

IEEE Computer Society

Location

Belgrade

ISBN

978-1-4799-6779-7

Book

IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits and Systems

Pages from

157

Pages to

160

Pages count

4

BibTex

@inproceedings{BUT119876,
  author="Martin {Krčma} and Jan {Kaštil} and Zdeněk {Kotásek}",
  title="Mapping trained neural networks to FPNNs",
  booktitle="IEEE 18th International Symposium on Design and Diagnostics of Electronic Circuits and Systems",
  year="2015",
  pages="157--160",
  publisher="IEEE Computer Society",
  address="Belgrade",
  doi="10.1109/DDECS.2015.50",
  isbn="978-1-4799-6779-7"
}