Microelectronics, Volume. 51, Issue 6, 905(2021)
Hardware Implementation of Tanh Function Based on Second-Order Approximation and Error Compensation
[1] [1] RAMANAIAH K V, SRIDHAR S. Hardware implementation of artificial neural networks [J]. I-Manager’s J Embedded Syst, 2014, 3(4): 31-34.
[2] [2] SHARMA S, ATHAIYA A. Activation functions in neural networks [J]. Int J Engineer Appl Sci Tech, 2020, 4(12): 310-316.
[3] [3] LEBOEUF K, NAMIN A H, MUSCEDERE R, et al. High speed VLSI implementation of the hyperbolic tangent sigmoid function [C] // 3rd Int Conf Convergence Hybrid Inform Tech. Busan, South Korea. 2008: 1070-1073.
[5] [5] LIN C W, WANG J S. A digital circuit design of hyperbolic tangent sigmoid function for neural networks [C] // IEEE ISCAS. Seattle, WA, USA. 2008: 856-859.
[7] [7] HAJDUK Z. Hardware implementation of hyperbolic tangent and sigmoid activation functions [J]. Bulletin Polish Academy Sci-Tech Sci, 2018, 66(5): 563-577.
[9] [9] SARANYA S, ELANGO B. Implementation of PWL and LUT based approximation for hyperbolic tangent activation function in VLSI [C] // Int Conf Commun Signal Process. Melmaruvathur, India. 2014: 1778-1782.
[10] [10] NAMIN A H, LEBOEUF K, MUSCEDERE R, et al. Efficient hardware implementation of the hyperbolic tangent sigmoid function [C] // IEEE Int Symp Circ Syst. Taiwan, China. 2009: 2117-2120.
[11] [11] LI Z, WANG L, GUO S, et al. Laius: an 8-bit fixed-point CNN hardware inference engine [C] // IEEE ISPA/IUCC. Guangzhou, China. 2017: 143-150.
[12] [12] ZAMANLOOY B, MIRHASSANI M. Efficient VLSI implementation of neural networks with hyperbolic tangent activation function [J]. IEEE Trans VLSI Syst, 2014, 22(1): 39-48.
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ZHANG Bowen, CHEN Gang, CHEN Xu, LU Huaxiang. Hardware Implementation of Tanh Function Based on Second-Order Approximation and Error Compensation[J]. Microelectronics, 2021, 51(6): 905
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Received: Jan. 14, 2021
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Published Online: Feb. 14, 2022
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