Parallel Batch Pattern Training of Recirculation Neural Network

Volodymyr Turchenko, Vladimir Golovko, Anatoly Sachenko

2012

Abstract

The development of a parallel batch pattern back propagation training algorithm of a recirculation neural network is presented in this paper. The model of a recirculation neural network and usual sequential batch pattern algorithm of its training are theoretically described. An algorithmic description of the parallel version of the batch pattern training method is presented. The parallelization efficiency of the developed parallel algorithm is investigated on the example of data compression and principal component analysis. The results of the experimental researches show that the developed parallel algorithm provides high parallelization efficiency on a parallel symmetric multiprocessor computer system. It allows applying the developed parallel software for the facilitation of scientific research of neural network-based intrusion detection system for computer networks.

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Paper Citation


in Harvard Style

Turchenko V., Golovko V. and Sachenko A. (2012). Parallel Batch Pattern Training of Recirculation Neural Network . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2012) ISBN 978-989-8565-21-1, pages 644-650. DOI: 10.5220/0004150206440650

in Bibtex Style

@conference{anniip12,
author={Volodymyr Turchenko and Vladimir Golovko and Anatoly Sachenko},
title={Parallel Batch Pattern Training of Recirculation Neural Network},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2012)},
year={2012},
pages={644-650},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004150206440650},
isbn={978-989-8565-21-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ANNIIP, (ICINCO 2012)
TI - Parallel Batch Pattern Training of Recirculation Neural Network
SN - 978-989-8565-21-1
AU - Turchenko V.
AU - Golovko V.
AU - Sachenko A.
PY - 2012
SP - 644
EP - 650
DO - 10.5220/0004150206440650