FPGA Implementation of Differential Evaluation Algorithm for MLP Training

Abstract

In this work, Differential Evolution Algorithm (DEA) is implemented on an embedded systems based on FPGA for the training of multi-layer perceptron (MLP). The classification performance of the MLP trained by DEA on FPGA has been analyzed by using a non-linear database. The MLP performance on FPGA has been compared with that on MATLAB in terms of computational performance and test accuracy. It is proved that DEA is suitable for realizing on FPGA considering simplicity of the algorithm. Simulation results of each component for DEA on FPGA are demonstrated in this paper.