A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data

Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Bin-Hua Zhao, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun

Abstract: Highlights•Core tensor sparsity of a Tucker-2 model is enhanced in a particular Tucker-3 model.•Orthogonality constraint is imposed on the third mode matrix to remove cross-talks.•The proposed model is solved by ADMM and HQS using tensor flattening method.•The proposed method improves estimations of non-sparse spatial components.•Novel features of cross-subject relationship increase the classification accuracy.