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Two-steps implementation of sigmoid function for artificial neural network in field programmable gate array

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Title: Two-steps implementation of sigmoid function for artificial neural network in field programmable gate array

Authors: Syahrulanuar Ngah, Rohani Abu Bakar, Abdullah Embong, Saifudin Razali

Journal: ARPN Journal of Engineering and Applied Sciences

HEC Recognition History
Category From To
Y 2023-07-01 2024-09-30
Y 2022-07-01 2023-06-30
Y 2021-07-01 2022-06-30
X 2020-07-01 2021-06-30

Publisher: Khyber Medical College, Peshawar

Country: Pakistan

Year: 2016

Volume: 11

Issue: 7

Language: English

Keywords: ANNFPGAsigmoid functiondLUTSONF

Categories
VLSI (15) Electrical Engineering (5972) Field-Programmable Gate Arrays (11) Sigmoid Function (1) Artificial Neural Networks (61)

Abstract

The complex equation of sigmoid function is one of the most difficult problems encountered for implementing the artificial neural network (ANN) into a field programmable gate array (FPGA). To overcome this problem, the combination of second order nonlinear function (SONF) and the differential lookup table (dLUT) has been proposed in this paper. By using this two-steps approach, the output accuracy achieved is ten times better than that of using only SONF and two times better than that of using conventional lookup table (LUT). Hence, this method can be used in various applications that required the implementation of the ANN into FPGA.

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