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 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.