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本文采用ZnO忆阻器模拟了生物神经突触的记忆和学习功能。ZnO突触器件表现出典型的随时间指数衰减的突触后兴奋电流(EPSC),以及EPSC的双脉冲增强行为。在此基础上,实现了学习-遗忘-再学习的经验式学习行为,以及四种不同种类的电脉冲时刻依赖可塑性学习规则。ZnO突触器件实现了超低能耗操作,单次突触行为能耗最低为1.6pJ,表明其可以用来构筑未来的人工神经网络硬件系统,最终开发出与人脑结构类似的认知型计算机以及类人机器人。
In this paper, ZnO memristor was used to simulate the memory and learning function of biological synapses. ZnO synaptic devices exhibit a typical exponential decay of the postsynaptic excited current (EPSC) over time, and the double pulse enhancement behavior of the EPSC. On this basis, learning-forgetting-re-learning is realized, and four different kinds of electrical impulses depend on the rules of plastic learning. ZnO synaptic device to achieve ultra-low power operation, a single synaptic behavior of the lowest energy consumption of 1.6pJ, indicating that it can be used to build the future of artificial neural network hardware system, and ultimately the development of human brain structure similar to the cognitive computer And humanoid robot.