Mixed-mode artificial neuron for CMOS integration

被引：0

作者：

Zatorre, Guillermo ^{[1
]}

Medrano, Nicolas ^{[1
]}

Sanz, M. Teresa ^{[1
]}

Martinez, Pedro A. ^{[1
]}

Celma, Santiago ^{[1
]}

机构：

[1] Univ Zaragoza, Grp Diseno Elect, Fac Ciencias, Zaragoza, Spain

来源：

CIRCUITS AND SYSTEMS FOR SIGNAL PROCESSING , INFORMATION AND COMMUNICATION TECHNOLOGIES, AND POWER SOURCES AND SYSTEMS, VOL 1 AND 2, PROCEEDINGS | 2006年

关键词：

D O I：

10.1109/MELCON.2006.1653118

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：

A new approach to designing artificial neurons in CMOS technology is proposed in this paper. Design and simulation results of the basic building blocks are presented. Programmable weights are obtained using a current-mode mixed-signal four-quadrant multiplier, whereas the non-linear output function is implemented with a specifically designed class AB current conveyor. Starting from circuit simulation results, the behaviour of the proposed neuron was modeled. A Multilayer Perceptron Network implemented with the new artificial neuron structure was trained to tackle linearization of a Giant Magneto-Resistive sensor. Simulation results show the efficiency of the new implementation.

引用

页码：381 / 384

页数：4

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