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.
Keywords
Field-programmable gate array
Computer science
MATLAB
Perceptron
Algorithm
Multilayer perceptron
Component (thermodynamics)
Artificial intelligence
Artificial neural network
Embedded system
Parallel computing
Operating system
Subject Areas
Neural Networks and Applications
·Artificial Intelligence ·Physical Sciences
Metaheuristic Optimization Algorithms Research
·Artificial Intelligence ·Physical Sciences
Blind Source Separation Techniques
·Signal Processing ·Physical Sciences
Citations by Year
2016: 2
2019: 1
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