反脉冲时间依赖可塑性学习机制的光学实现
发布时间：2018-08-08 14:51
【摘要】：突触可塑性为神经网络的学习机制提供了基础。基于单个半导体光放大器(SOA)的非线性偏振旋转(NPR)和交叉增益调制(XGM)效应实现了反脉冲时间依赖可塑性(anti-STDP)学习机制。通过调整SOA驱动电流,可以实现长时程增强窗口(LTP)和长时程抑制窗口(LTD)的高度和宽度调整,能更好地模拟神经网络。实验测量得到的anti-STDP曲线与生物系统中测量得到的学习曲线相吻合。使用该anti-STDP光路得到的学习曲线的时间窗口约为几百皮秒,其速度是人类大脑STDP学习机制的108倍。由于该anti-STDP光路系统简单,且SOA易于与其他器件集成,该anti-STDP光路可以用于实现大规模超快神经拟态计算系统。
[Abstract]:Synaptic plasticity provides the basis for the learning mechanism of neural networks. Based on the nonlinear polarization rotated (NPR) and cross-gain modulated (XGM) effect of a single semiconductor optical amplifier (SOA), the anti-pulse time-dependent plasticity (anti-STDP) learning mechanism is realized. By adjusting the driving current of SOA, the height and width of (LTP) and (LTD) can be adjusted, and the neural network can be simulated better. The anti-STDP curve obtained from the experiment is in agreement with the learning curve obtained in the biological system. The time window of the learning curve obtained by using the anti-STDP optical path is about a few hundred picoseconds, which is 108 times faster than the STDP learning mechanism of the human brain. Because the anti-STDP optical circuit system is simple and the SOA is easy to integrate with other devices, the anti-STDP optical path can be used to realize the large-scale ultra-fast neural pseudo computing system.
【作者单位】： 北京交通大学理学院光信息科学与技术研究所发光与光信息技术教育部重点实验室;北京交通大学电气工程学院;
【基金】：国家自然科学基金(61571035,61401017,61378061)
【分类号】：TN248.4
[Abstract]:Synaptic plasticity provides the basis for the learning mechanism of neural networks. Based on the nonlinear polarization rotated (NPR) and cross-gain modulated (XGM) effect of a single semiconductor optical amplifier (SOA), the anti-pulse time-dependent plasticity (anti-STDP) learning mechanism is realized. By adjusting the driving current of SOA, the height and width of (LTP) and (LTD) can be adjusted, and the neural network can be simulated better. The anti-STDP curve obtained from the experiment is in agreement with the learning curve obtained in the biological system. The time window of the learning curve obtained by using the anti-STDP optical path is about a few hundred picoseconds, which is 108 times faster than the STDP learning mechanism of the human brain. Because the anti-STDP optical circuit system is simple and the SOA is easy to integrate with other devices, the anti-STDP optical path can be used to realize the large-scale ultra-fast neural pseudo computing system.
【作者单位】： 北京交通大学理学院光信息科学与技术研究所发光与光信息技术教育部重点实验室;北京交通大学电气工程学院;
【基金】：国家自然科学基金(61571035,61401017,61378061)
【分类号】：TN248.4
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