Implementation of a modular neural network in a multiple processor system on FPGA to classify electric disturbance

This paper shows the effectiveness of a modular neural network composed of multilayers experts trained with a hybrid algorithm implemented in a multiprocessor system on chip. The network is applied on the classification of electric disturbances. The objective is to show that, even a FPGA with hardwa...

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Bibliographic Details
Published in2009 35th Annual Conference of IEEE Industrial Electronics pp. 2081 - 2086
Main Authors Lopes, D.C., Magalhaes, R.M., Melo, J.D., Neto, A.D.D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.11.2009
Subjects
Discrete wavelet transforms
Field programmable gate arrays
Machine learning
Multi-layer neural network
Multilayer perceptrons
Neural networks
Neurons
Parallel processing
Pattern classification
System-on-a-chip
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Summary:This paper shows the effectiveness of a modular neural network composed of multilayers experts trained with a hybrid algorithm implemented in a multiprocessor system on chip. The network is applied on the classification of electric disturbances. The objective is to show that, even a FPGA with hardware restrictions, it could be used to implement a complex problem, when parallel processing is used. To improve the system performance was used four soft processors with a shared memory.
ISBN:9781424446483
1424446481
ISSN:1553-572X
DOI:10.1109/IECON.2009.5415103