突触
峰值时间相关塑性
长时程增强
Spike(软件开发)
神经形态工程学
神经科学
突触重量
计算机科学
突触可塑性
电阻式触摸屏
可塑性
人工神经网络
材料科学
人工智能
化学
生物
软件工程
计算机视觉
复合材料
生物化学
受体
作者
S. G. Hu,H. T. Wu,Y. Liu,T. P. Chen,Z. Liu,Qi Yu,You Yin,Sumio Hosaka
摘要
This paper presents a design of electronic synapse with Spike Time Dependent Plasticity (STDP) based on resistive memory device. With the resistive memory device whose resistance can be purposely changed, the weight of the synaptic connection between two neurons can be modified. The synapse can work according to the STDP rule, ensuring that the timing between pre and post-spikes leads to either the long term potentiation or long term depression. By using the synapse, a neural network with three neurons has been constructed to realize the STDP learning.
科研通智能强力驱动
Strongly Powered by AbleSci AI