Implementation and Evaluation of Modular Neural Networks in a Multiple Processor System on Chip to Classify Electric Disturbance

This paper shows the effectiveness of modular neural networks 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 hardwar...

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Bibliographic Details
Published in2009 International Conference on Computational Science and Engineering Vol. 1; pp. 412 - 417
Main Authors Lopes, D.C., Magalhaes, R.M., Melo, J.D., Neto, A.D.D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.08.2009
Subjects
Artificial neural networks
Field programmable gate arrays
Function approximation
Machine learning
Multi-layer neural network
Multilayer perceptrons
Neural networks
Parallel processing
Pattern classification
System-on-a-chip
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Summary:This paper shows the effectiveness of modular neural networks 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, 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:9781424453344
1424453348
DOI:10.1109/CSE.2009.36