Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array

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 look...

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Main Authors:	Syahrulanuar, Ngah, Rohani, Abu Bakar, Abdullah, Embong, Saifudin, Razali
Format:	Article
Language:	English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://umpir.ump.edu.my/id/eprint/24854/ http://umpir.ump.edu.my/id/eprint/24854/ http://umpir.ump.edu.my/id/eprint/24854/1/Two-Steps%20Implementation%20of%20Sigmoid%20Function%20for%20Artificial%20Neural%20Network%20in%20Field%20Programmable%20Gate%20Array.pdf

id	ump-24854
recordtype	eprints
spelling	ump-248542019-05-15T06:30:29Z http://umpir.ump.edu.my/id/eprint/24854/ Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array Syahrulanuar, Ngah Rohani, Abu Bakar Abdullah, Embong Saifudin, Razali QA75 Electronic computers. Computer science 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. Asian Research Publishing Network (ARPN) 2016 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/24854/1/Two-Steps%20Implementation%20of%20Sigmoid%20Function%20for%20Artificial%20Neural%20Network%20in%20Field%20Programmable%20Gate%20Array.pdf Syahrulanuar, Ngah and Rohani, Abu Bakar and Abdullah, Embong and Saifudin, Razali (2016) Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array. ARPN Journal of Engineering and Applied Sciences, 11 (7). pp. 4882-4888. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0416_4041.pdf
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Syahrulanuar, Ngah Rohani, Abu Bakar Abdullah, Embong Saifudin, Razali Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
description	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.
format	Article
author	Syahrulanuar, Ngah Rohani, Abu Bakar Abdullah, Embong Saifudin, Razali
author_facet	Syahrulanuar, Ngah Rohani, Abu Bakar Abdullah, Embong Saifudin, Razali
author_sort	Syahrulanuar, Ngah
title	Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
title_short	Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
title_full	Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
title_fullStr	Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
title_full_unstemmed	Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array
title_sort	two-steps implementation of sigmoid function for artificial neural network in field programmable gate array
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/24854/ http://umpir.ump.edu.my/id/eprint/24854/ http://umpir.ump.edu.my/id/eprint/24854/1/Two-Steps%20Implementation%20of%20Sigmoid%20Function%20for%20Artificial%20Neural%20Network%20in%20Field%20Programmable%20Gate%20Array.pdf
first_indexed	2023-09-18T22:37:51Z
last_indexed	2023-09-18T22:37:51Z
_version_	1777416716294291456

Two-Steps Implementation of Sigmoid Function for Artificial Neural Network in Field Programmable Gate Array

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