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FPGA implementation of Differential Evaluation Algorithm for MLP training

机译:MLP训练差分评估算法的FPGA实现

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摘要

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.
机译:在这项工作中,在基于FPGA的嵌入式系统上实现了差分进化算法(DEA),用于训练多层感知器(MLP)。使用非线性数据库分析了DEA在FPGA上训练的MLP的分类性能。在计算性能和测试准确性方面,已将FPGA上的MLP性能与MATLAB上的MLP性能进行了比较。考虑到算法的简单性,证明DEA适合在FPGA上实现。本文展示了DEA在FPGA上每个组件的仿真结果。

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