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논문 기본 정보

저자정보
(Seoul National University) (Seoul National University) (Seoul National University)
저널정보
대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.22 No.2
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    초록·키워드

    To process data operations more efficiently in deep neural networks (DNNs), studies on spiking neural networks (SNNs) have been conducted. In the reported literature, CMOS neuron circuits that mimic the biological behavior of an integrate-and-fire function of neurons have been mainly studied. Because conventional neuronal circuits need to be improved in terms of area and energy consumption, neuron devices with memory functions such as resistive random access memory (RRAM), phase-change random access memory (PCRAM), magnetic random access memory (MRAM), floating body FETs, and ferroelectric FETs have been emerged to replace a membrane capacitor and trigger device in the conventional neuron circuits. In this review article, neuron devices that can increase the integration density of conventional neuronal circuits and reduce power consumption are reviewed. These devices are expected to play an important role in future neuromorphic systems.

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      UCI(KEPA) : I410-ECN-0101-2022-569-001135988