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

页码：379 / 383

页数：5

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