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...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Asian Research Publishing Network (ARPN)
2016
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| Online Access: | 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 |
| _version_ | 1848822139567734784 |
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| 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 |
| building | UMP Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T02:36:30Z |
| format | Article |
| id | ump-24854 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:36:30Z |
| publishDate | 2016 |
| publisher | Asian Research Publishing Network (ARPN) |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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. (Published) http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0416_4041.pdf |
| 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 |
| title | 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_short | 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 |
| topic | QA75 Electronic computers. Computer science |
| 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 |