Extracting multi-mode ERP features using fifth-order nonnegative tensor decomposition

• Published in: Journal of neuroscience methods Vol. 308; pp. 240 - 247
• Main Authors: Wang, Deqing, Zhu, Yongjie, Ristaniemi, Tapani, Cong, Fengyu
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.10.2018
• Subjects: CANDECOMP/PARAFAC; Component number selection; Event-related potential; Multi-mode features; Nonnegative tensor decomposition; Event-related potential; Component number selection; CANDECOMP/PARAFAC; Multi-mode features; Nonnegative tensor decomposition

Preprocessed Event-related potential (ERP) data are usually organized in multi-way tensor, in which tensor decomposition serves as a powerful tool for data processing. Due to the limitation of computation burden for multi-way data and the low algorithm performance of stability and efficiency, multi-...