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作 者:Xinhuang Lin Haotian Long Shuo Ke Yuyuan Wang Ying Zhu Chunsheng Chen Changjin Wan Qing Wan 林鑫煌;龙昊天;柯硕;王宇远;祝影;陈春生;万昌锦;万青(School of Electronic Science and Engineering,Nanjing University,Nanjing 210093,China)
机构地区:[1]School of Electronic Science and Engineering,Nanjing University,Nanjing 210093,China
出 处:《Chinese Physics Letters》2022年第6期1-4,共4页中国物理快报(英文版)
基 金:supported by the National Key Research and Development Program of China (Grant No. 2019YFB2205400);the National Natural Science Foundation of China (Grant No. 62074075)
摘 要:The human brain that relies on neural networks communicated by spikes is featured with ultralow energy consumption, which is more robust and adaptive than any digital system. Inspired by the spiking framework of the brain, spike-based neuromorphic systems have recently inspired intensive attention. Therefore, neuromorphic devices with spike-based synaptic functions are considered as the first step toward this aim. Photoelectric neuromorphic devices are promising candidates for spike-based synaptic devices with low latency, broad bandwidth,and superior parallelism. Here, the indium-gallium-zinc-oxide-based photoelectric neuromorphic transistors are fabricated for Morse coding based on spike processing, 405-nm light spikes are used as synaptic inputs, and some essential synaptic plasticity, including excitatory postsynaptic current, short-term plasticity, and high-pass filtering, can be mimicked. More interestingly, Morse codes encoded by light spikes are decoded using our devices and translated into amplitudes. Furthermore, such devices are compatible with standard integrated processes suitable for large-scale integrated neuromorphic systems.
分 类 号:TN36[电子电信—物理电子学]
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