Title: Dual-processor neural network implementation in fpga
Authors: Morgado Dias , Diego Santos, Henrique Nunes
Abstract: Artificial Neural Networks have become a common solution for many real world problems. Many industrial, commercial and research applications need hardware implementation due to issues regarding stability, speed, price and size. This paper presents the implementation of a feed forward Artificial Neural Network in FPGA using two embedded processors. The processors used are Xilinx hardcore PowerPCs. To verify the implementation developed, a control loop of Direct Inverse Control was simulated using a Personal Computer and a FPGA, thereby implementing a direct and an inverse model of a system, respectively. The results obtained show that the hardware implementation works properly and introduces no additional error.
Publication date: 2012-07-16
Online entry date: 2013-05-08
Conference: CONTROLO’2012
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