Learn More
Hu et al. [4] recently proposed two-dimensional locality preserving projections (2DLPP) for image feature extraction. The 2DLPP was directly based on image matrices rather than vectors and thus obviated the transformation from matrices to vectors as usually performed in LPP. Although the effectiveness of 2DLPP has been shown by experiments, we will show in(More)
BACKGROUND Dysfunctional integration of distributed brain networks is believed to be the cause of schizophrenia, and resting-state functional connectivity analyses of schizophrenia have attracted considerable attention in recent years. Unfortunately, existing functional connectivity analyses of schizophrenia have been mostly limited to linear associations.(More)
Separating brain imaging signals by maximizing their autocorrelations is an important component of blind source separation (BSS). Canonical correlation analysis (CCA), one of leading BSS techniques, has been widely used for analyzing optical imaging (OI) and functional magnetic resonance imaging (fMRI) data. However, because of the need to reduce(More)