神经形态应用Hf0.5Zr0.5O2/Si效应场效应油藏计算的提出与实验论证

2020 IEEE Symposium on VLSI Technology Pub Date : 2020-06-01 DOI:10.1109/VLSITechnology18217.2020.9265110

E. Nako, K. Toprasertpong, R. Nakane, Z. Wang, Y. Miyatake, M. Takenaka, S. Takagi

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引用次数: 17

摘要

我们提出了一种新的人工智能计算方案，利用铁电栅mosfet (fefet)的记忆效应和非线性，用于神经形态应用。以栅极电压输入漏极电流的时间响应为虚拟节点，实验验证了时序数据的任务运算。实验验证了对输入数据的高分类能力。

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Proposal and Experimental Demonstration of Reservoir Computing using Hf0.5Zr0.5O2/Si FeFETs for Neuromorphic Applications

We propose a new AI calculation scheme by reservoir computing utilizing the memory effect and nonlinearity of ferroelectric gate MOSFETs (FeFETs) for neuromorphic applications. The task operations of time-series data are experimentally demonstrated by taking time responses of the drain current for gate voltage input as the virtual nodes. A high ability to classify input data is experimentally verified.

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2020 IEEE Symposium on VLSI Technology

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