FPGA implementation of Differential Evaluation Algorithm for MLP training

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 ha...

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Bibliographic Details
Published in:	2014 IEEE International Symposium on Innovations in Intelligent Systems and Applications (INISTA) Proceedings pp. 425 - 430
Main Authors:	Yilmaz, Ali Riza, Erkmen, Burcu, Yavuz, Oguzhan
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01-06-2014
Subjects:	Biological cells Differential Evolution Algorithm Field programmable gate arrays FPGA Heuristic algorithms MLP Training Sociology Statistics Training Vectors
Online Access:	Get full text
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Summary:	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.
DOI:	10.1109/INISTA.2014.6873655