神经形态工程学
记忆电阻器
突触后电位
突触重量
长时程增强
材料科学
传输(电信)
计算机科学
光电子学
化学
电子工程
人工神经网络
人工智能
工程类
电信
生物化学
受体
作者
Junlin Yue,Lanqing Zou,Na Bai,Chuqian Zhu,Yunhui Yi,Xue Fan,Huajun Sun,Shane Hu,Weiming Cheng,Qiang He,Hong-Liang Lü,Lei Ye,Xiangshui Miao
标识
DOI:10.1002/smtd.202301657
摘要
Abstract Memristor possesses great potential and advantages in neuromorphic computing, while consistency and power consumption issues have been hindering its commercialization. Low cost and accuracy are the advantages of human brain, so memristors can be used to construct brain‐like synaptic devices to solve these problems. In this work, a five‐layer AlO x device with a V‐shaped oxygen distribution is used to simulate biological synapses. The device simulates synapse structurally. Further, under electrical stimulation, O 2− moves to the Ti electrode and oxygen vacancy (V o ) moves to the Pt electrode, thus forming a conductive filament (CF), which simulates the Ca 2+ flow and releases neurotransmitters to the postsynaptic membrane, thus realizing the transmission of information. By controlling applied voltage, the regulation of Ca 2+ gated pathway is realized to control the Ca 2+ internal flow and achieve different degrees of information transmission. Long‐term Potentiation (LTP)/Long‐term Depression (LTD), Spike Timing Dependent Plasticity (STDP), these basic synaptic performances can be simulated. The AlO x device realizes low power consumption (56.7 pJ/392 fJ), high switching speed (25 ns/60 ns), and by adjusting the window value, the nonlinearity is improved (0.133/0.084), a high recognition accuracy (98.18%) is obtained in neuromorphic simulation. It shows a great prospect in multi‐value storage and neuromorphic computing.
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