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

Author

Lopes, Danniel C. ; Magalhães, Rafael M. ; Melo, Jorge D. ; Neto, A.D.D.

Author_Institution

UFERSA Univ. Fed. of Semi Arido, Mossoro, Brazil

Volume

1

fYear

2009

fDate

29-31 Aug. 2009

Firstpage

412

Lastpage

417

Abstract

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.

Keywords

microprocessor chips; multiprocessing systems; neural nets; parallel algorithms; electric disturbance classification; hybrid algorithm; modular neural networks; multiprocessor system on chip; parallel processing; shared memory; soft processor; 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;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Science and Engineering, 2009. CSE '09. International Conference on

Conference_Location

Vancouver, BC

Print_ISBN

978-1-4244-5334-4

Electronic_ISBN

978-0-7695-3823-5

Type

conf

DOI

10.1109/CSE.2009.36

Filename

5283349