Design of An Analog Circuit-Based Artificial Neural Network

被引：0
|
作者：
Gencer, Fikret Basar [1 ]
Xhafa, Xhesila [1 ]
Inam, Benan Beril [1 ]
Yelten, Mustafa Berke [1 ]
机构：
[1] Istanbul Tech Univ, Elect & Communucat Engn, Istanbul, Turkey
来源：
2019 11TH INTERNATIONAL CONFERENCE ON ELECTRICAL AND ELECTRONICS ENGINEERING (ELECO 2019) | 2019年
关键词：
LOW-POWER;
D O I：
10.23919/eleco47770.2019.8990559
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 paper, a feed-forward artificial neural network with a single hidden layer has been realized using analog circuit blocks designed in 90 nm UMC technology. The network is capable of solving non-linearly separable problems and successfully realizes the XOR gate, which is one of the most basic and common non-linear classification problems. The inputs and the weights of the network are represented by the amplitudes of the transient signals. The weights have been calculated through the back-propagation (BP) algorithm. The analog circuit-based learning implementation yields accurate results with the expected outputs.
引用
收藏
页码：379 / 383
页数：5
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