A digital circuit design of hyperbolic tangent sigmoid function for neural networks

研究成果: Conference contribution

36 引文 斯高帕斯(Scopus)

摘要

This paper presents a digital circuit design approach for a commonly used activation function, hyperbolic tangent sigmoid functions, for neural networks. Our design concept for such a nonlinear function is to approximate the function of its first-order derivative by piece-wise linear functions first, then to obtain the estimate of the original function by integrating the approximated function of the first-order derivative by a digital circuit. The average error and maximum error of the proposed approximation approach are in the order of 10-3 and 10-2, respectively in the software simulation. The hardware implementation of the proposed method consumes only one multiplication and one addition/subtraction ALU with the aid of resource sharing. The performance of our circuit has been validated by a neural network for a system identification problem in the software simulation.

原文English
主出版物標題2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
頁面856-859
頁數4
DOIs
出版狀態Published - 2008 九月 19
事件2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008 - Seattle, WA, United States
持續時間: 2008 五月 182008 五月 21

出版系列

名字Proceedings - IEEE International Symposium on Circuits and Systems
ISSN(列印)0271-4310

Other

Other2008 IEEE International Symposium on Circuits and Systems, ISCAS 2008
國家United States
城市Seattle, WA
期間08-05-1808-05-21

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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