仿生神经计算用全固态离子掺杂突触晶体管

Q. Wang, C. Zhao, W. Liu, H. Zalinge, Y. Liu, L. Yang, C. Zhao
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引用次数: 1

摘要

人工突触是低功耗神经形态计算的关键组成部分,它超越了冯·诺伊曼结构的限制。与具有成线和电荷捕获机制的双端忆阻器和三端晶体管相比,新兴的电解门控晶体管(EGT)由于其出色的模拟开关性能而被证明是一种有前途的神经形态应用。候选人。本文提出了一种新型的低温溶液型氧化物薄膜晶体管,该晶体管采用离子掺杂的介电层。该器件还具有低噪声线性电导更新和相对较高的Gmax/Gmin。神经形态计算的实现具有接近理想的精度。这些结果突出了基于AlOx-Li/InOx薄膜晶体管的EGT在冯·诺伊曼架构之外的下一代低功耗电子产品中的潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
All-solid-state Ion Doping Synaptic Transistor for Bionic Neural computing
Artificial synapses are the critical component for low-power neuromorphic computing, which surpasses the limitations of von Neumann’s structure. Compared with two-terminal memristors and three-terminal transistors with wire formation and charge trapping mechanisms, the emerging electrolytic gated transistor (EGT) has proven to be a promising neuromorphic application due to its outstanding analog switching performance. Candidate. This paper presents a new low-temperature solution-based oxide thin film transistor, which uses an ion-doped dielectric layer. The device also has a low-noise linear conductance update and a relatively high Gmax/Gmin. The realization of ANN neuromorphic calculation has nearly ideal accuracy. These results highlight the potential of EGT based on AlOx-Li/InOx thin-film transistors in the next generation of low-power electronics outside of the von Neumann architecture.
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