The invention discloses a random grouping method for large-scale fMRI data
coupling tensor decomposition, and belongs to the field of
biomedical signal processing. The method comprises the following steps: firstly, randomly scrambling the sequence of all subjects, then carrying out equal-size sub-
tensor division, and carrying out first-round
decomposition by adopting a space
coupling Tucker decomposition method; next, circularly moving left for several subjects, performing equal-size sub-
tensor division again to form a new
subject group, and performing a second round of space
coupling Tucker decomposition; and analogy is carried out in sequence until displacement, sub-tensor division and space coupling
Tucker decomposition of a predetermined round are completed, and
decomposition results of group common and individual specific characteristics are obtained. According to the method, the
adverse effect of the initial arrangement sequence of the large-scale subjects on
feature extraction is weakened, the overall performance of the coupling
tensor decomposition method is remarkably improved, especially the
noise of networks such as
central vision is reduced, and better feature support can be provided for
brain function research and objective marker extraction of neuropsychiatric brain diseases.