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 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.