论文标题
通过学习相位振幅耦合来增强生物信号分类中的概括
Boosting Generalization in Bio-Signal Classification by Learning the Phase-Amplitude Coupling
论文作者
论文摘要
生物信号的各种手工制作的特征表示主要依赖于特定频带中信号的振幅或功率。相分量通常比幅度更具体，因此对噪声更敏感，因此通常会丢弃相分量。但是，通常，相分量还具有与潜在的生物过程相关的信息。实际上，在本文中，我们显示了学习生物信号的相位和振幅成分的耦合的好处。我们通过引入一项新型的自我监督学习任务来做到这一点，我们称之为相关，该任务可以通过合并不同来源的幅度和相位来检测生物信号。我们在评估中表明，接受该任务的神经网络跨科目和记录会议的训练比完全监督的对应者更好地推广。
Various hand-crafted features representations of bio-signals rely primarily on the amplitude or power of the signal in specific frequency bands. The phase component is often discarded as it is more sample specific, and thus more sensitive to noise, than the amplitude. However, in general, the phase component also carries information relevant to the underlying biological processes. In fact, in this paper we show the benefits of learning the coupling of both phase and amplitude components of a bio-signal. We do so by introducing a novel self-supervised learning task, which we call Phase-Swap, that detects if bio-signals have been obtained by merging the amplitude and phase from different sources. We show in our evaluation that neural networks trained on this task generalize better across subjects and recording sessions than their fully supervised counterpart.
