论文标题
带有反馈电流的Spintronics水库中内存功能的周期性结构
Periodic structure of memory function in spintronics reservoir with feedback current
论文作者
论文摘要
从理论上研究了反馈效应对物理储层计算的作用，通过求解纳米结构的铁磁体中的涡旋核动力学来研究。尽管由于反馈电流引起的自旋转移扭矩使涡流动力学复杂化，但可以澄清的是，反馈效应并不总是有助于增强物理储层中的内存函数。记忆函数的特征是当反馈电流的延迟时间不是脉冲宽度的积分倍数时，输入数据与涡流核心的动态响应之间的相关系数变得很大。另一方面，当延迟时间是脉冲宽度的积分倍数时，内存函数仍然很小。结果，相对于延迟时间，观察到短期记忆能力的周期性行为，其现象可以归因于通过反馈电流的虚拟神经元之间的相关性。
The role of the feedback effect on physical reservoir computing is studied theoretically by solving the vortex-core dynamics in a nanostructured ferromagnet. Although the spin-transfer torque due to the feedback current makes the vortex dynamics complex, it is clarified that the feedback effect does not always contribute to the enhancement of the memory function in a physical reservoir. The memory function, characterized by the correlation coefficient between the input data and the dynamical response of the vortex core, becomes large when the delay time of the feedback current is not an integral multiple of the pulse width. On the other hand, the memory function remains small when the delay time is an integral multiple of the pulse width. As a result, a periodic behavior for the short-term memory capacity is observed with respect to the delay time, the phenomenon of which can be attributed to correlations between the virtual neurons via the feedback current.
