论文标题
强制STNO网络的频相潜力：诱发记忆的示例
A Frequency-Phase Potential for a Forced STNO Network: an Example of Evoked Memory
论文作者
论文摘要
此处研究的网络基于物理学的标准模型，但它出现在从旋转技术到神经科学的各种应用中。当网络被其所有元素共有的外部信号强迫时，显示出两个潜在的（梯度）函数：一个用于振幅，一个用于阶段。但是当删除强迫时，相位势会消失。相位电势描述了网络中的相/反相振荡的分布以及相位锁定形式的共振。潜在表面中的山谷对应于联想召回可以访问的记忆。这里得出的两个电势展示了两种不同形式的内存形式：在自由问题中持续的结构内存（时域存储器），并诱发记忆（频域存储器），这些内存是由相位电势持续的，只有在系统被常见的外部强迫照亮时才会出现。共同的强迫将网络组织到那些被锁定为强迫频率和其他可能形成僻静子网络的元素的元素中。僻静的网络可以执行独立操作，例如模式识别和逻辑计算。展示了用于塑造网络输出的各种控制方法。
The network studied here is based on a standard model in physics, but it appears in various applications ranging from spintronics to neuroscience. When the network is forced by an external signal common to all its elements, there are shown to be two potential (gradient) functions: One for amplitudes and one for phases. But the phase potential disappears when the forcing is removed. The phase potential describes the distribution of in-phase/anti-phase oscillations in the network, as well as resonances in the form of phase locking. A valley in a potential surface corresponds to memory that may be accessed by associative recall. The two potentials derived here exhibit two different forms of memory: structural memory (time domain memory) that is sustained in the free problem, and evoked memory (frequency domain memory) that is sustained by the phase potential, only appearing when the system is illuminated by common external forcing. The common forcing organizes the network into those elements that are locked to forcing frequencies and other elements that may form secluded sub-networks. The secluded networks may perform independent operations such as pattern recognition and logic computations. Various control methods for shaping the network's outputs are demonstrated.
