Multiplication-Free Neural Networks

被引：0
|
作者：
Akbas, Cem Emre [1 ]
Bozkurt, Alican [1 ]
Cetin, A. Enis [1 ]
Cetin-Atalay, Rengul [2 ]
Uner, Aysegul [3 ]
机构：
[1] Bilkent Univ, Elekt & Elekt Muhendisligi Bolumu, TR-06800 Ankara, Turkey
[2] Ortadogu Tekn Univ, Enformat Bolumu, TR-06800 Ankara, Turkey
[3] Hacettepe Univ, Tip Fak, TR-06100 Ankara, Turkey
来源：
2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年
关键词：
Artificial Neural Network; Multiplication-free Operator;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this article, a multiplication-free artificial Neural Network (ANN) structure is proposed. Inner products between the input vectors and the ANN weights are implemented using a multiplication-free vector operator. Training of the new artificial neural network structure is carried out using the sign-LMS algorithm. Proposed ANN system can be used in applications requiring low-power usage or running on microprocessors that have limited processing power.
引用
收藏
页码：2416 / 2418
页数：3
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