loading
Papers

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Dominic Just ; Jeferson F. Chaves ; Rogerio M. Gomes and Henrique E. Borges

Affiliation: CEFET-MG, Brazil

ISBN: 978-989-8425-32-4

Keyword(s): Spiking neural networks, Field programmable gate array (FPGA), Hardware design.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neural Network Hardware Implementation and Applications ; Neural Networks ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Theory and Methods

Abstract: Hardware implementations of spiking neuron models have been studied over the years mainly in researches focused on bio-inspired systems and computational neuroscience. This introduced considerable challenges for researchers particularly in terms of the requirements to realise a efficient embedded solution which may provide artificial devices adaptability and performance in real-time environment. Thus, programmable hardware was widely used as a model for the adaptable requirements of neural networks. From this perspective, this paper describes an efficient implementation of a realistic spiking neuron model on a Field Programmable Gate Array (FPGA). A network consisting of 10 Izhikevich’s neurons was produced, in a low-cost and low-density FPGA. It operates 100 times faster than in real time, and the perspectives of these results in newer models of FPGAs are promising.

PDF ImageFull Text

Download
CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.92.92.168

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Just, D.; F. Chaves, J.; M. Gomes, R. and E. Borges, H. (2010). AN EFFICIENT IMPLEMENTATION OF A REALISTIC SPIKING NEURON MODEL ON AN FPGA.In Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010) ISBN 978-989-8425-32-4, pages 344-349. DOI: 10.5220/0003084303440349

@conference{icnc10,
author={Dominic Just. and Jeferson F. Chaves. and Rogerio M. Gomes. and Henrique E. Borges.},
title={AN EFFICIENT IMPLEMENTATION OF A REALISTIC SPIKING NEURON MODEL ON AN FPGA},
booktitle={Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)},
year={2010},
pages={344-349},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003084303440349},
isbn={978-989-8425-32-4},
}

TY - CONF

JO - Proceedings of the International Conference on Fuzzy Computation and 2nd International Conference on Neural Computation - Volume 1: ICNC, (IJCCI 2010)
TI - AN EFFICIENT IMPLEMENTATION OF A REALISTIC SPIKING NEURON MODEL ON AN FPGA
SN - 978-989-8425-32-4
AU - Just, D.
AU - F. Chaves, J.
AU - M. Gomes, R.
AU - E. Borges, H.
PY - 2010
SP - 344
EP - 349
DO - 10.5220/0003084303440349

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.