Hardware Implementation of Backpropagation Neural Networks on Field programmable Gate Array (FPGA)

Section: Article
Published
Jul 28, 2008
Pages
62-70

Abstract

In this paper, a design method of neural networks based on VHDL hardware description language, and FPGA implementation is proposed. A design of a general neuron for topologies using backpropagation algorithm is described. The sigmoid nonlinear activation function is also implemented. The neuron is then used in the design and implementation of a neural network using Xilinx Spartan-3e FPGA. The simulation results obtained with Xilinx ISE 8.2i software. The results are analyzed in terms of operating frequency and chip utilization.Key words : Artificial, Neural , Network, Backprobagation, FPGA,VHDL.

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How to Cite

[1]
R. Ahmed Khalil and رافد, “Hardware Implementation of Backpropagation Neural Networks on Field programmable Gate Array (FPGA)”, AREJ, vol. 16, no. 3, pp. 62–70, Jul. 2008.