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Authors: Alessandro Cinti and Antonello Rizzi

Affiliation: University of Rome “La Sapienza”, Italy

ISBN: 978-989-8425-84-3

Keyword(s): Neural networks, Neurofuzzy networks, Hardware acceleration, Min-max classifiers, FPGA.

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

Abstract: Many industrial applications concerning pattern recognition techniques often demand to develop suited low cost embedded systems in charge of performing complex classification tasks in real time. To this aim it is possible to rely on FPGA for designing effective and low cost solutions. Among neurofuzzy classification models, Min-Max networks constitutes an interesting tool, especially when trained by constructive, robust and automatic algorithms, such as ARC and PARC. In this paper we propose a parallel implementation of a Min-Max classifier on FPGA, designed in order to find the best compromise between model latency and resources needed on the FPGA. We show that by rearranging the equations defining the adopted membership function for the hidden layer neurons, it is possible to substantially reduce the number of logic elements needed, without increasing the model latency, i.e. without any need to lower the classifier working frequency.

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Paper citation in several formats:
Cinti A. and Rizzi A. (2011). NEUROFUZZY MIN-MAX NETWORKS IMPLEMENTATION ON FPGA.In Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011) ISBN 978-989-8425-84-3, pages 51-57. DOI: 10.5220/0003680700510057

@conference{ncta11,
author={Alessandro Cinti and Antonello Rizzi},
title={NEUROFUZZY MIN-MAX NETWORKS IMPLEMENTATION ON FPGA},
booktitle={Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)},
year={2011},
pages={51-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003680700510057},
isbn={978-989-8425-84-3},
}

TY - CONF

JO - Proceedings of the International Conference on Neural Computation Theory and Applications - Volume 1: NCTA, (IJCCI 2011)
TI - NEUROFUZZY MIN-MAX NETWORKS IMPLEMENTATION ON FPGA
SN - 978-989-8425-84-3
AU - Cinti A.
AU - Rizzi A.
PY - 2011
SP - 51
EP - 57
DO - 10.5220/0003680700510057

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