Halfway Between CP and Tucker Model: PARALIND Analysis of Human Electroencephalogram

Abstract

Subject-specific narrowband oscillatory rhythms in human electroencephalogram (EEG) can be detected using tensor decomposition. In our previous studies, we explored the CANDE- COMP/PARAFAC (CP) decomposition together with the more flexible Tucker model. However , we found that CP decomposition sometimes required a high number of latent components to rep- resent the data latent structure accurately. On the other hand, the Tucker model appeared too generalized, leading to very sparse solutions. Therefore, in this study, we focus on the PARA- LIND model, which combines the more straightforward interpretability of CP decomposition with the flexibility o f t he Tucker m odel. We d emonstrate i ts p erformance o n E EG recordings from a patient following an ischemic stroke, comparing it to the previous two models.


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