High accuracy FPGA activation function implementation for neural networks

被引：21
|
作者：
Hajduk, Zbigniew [1 ]
机构：
[1] Rzeszow Univ Technol, Ul Powstancow Warszawy 12, PL-35959 Rzeszow, Poland
来源：
NEUROCOMPUTING | 2017年 / 247卷
关键词：
FPGA; Hyperbolic tangent; Sigmoid; Floating point arithmetic; HARDWARE IMPLEMENTATION;
D O I：
10.1016/j.neucom.2017.03.044
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This letter shortly presents an FPGA implementation method of the hyperbolic tangent and sigmoid activation functions for artificial neural networks. A kind of a direct implementation of the functions is proposed. The implementation results show that the obtained accuracy of the method is relatively high compared to other published solutions. (C) 2017 Elsevier B.V. All rights reserved.
引用
收藏
页码：59 / 61
页数：3
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