2017
Simultaneous low-rank component and graph estimation for high-dimensional graph signals: Application to brain imaging
ICASSP 2017accepted
We propose an algorithm to uncover the intrinsic low-rank component of a high-dimensional, graph-smooth and grossly-corrupted dataset, under the situations that the underlying graph is unknown. Based on a model with a low-rank component plus a sparse perturbation, and an initial graph estimation, ou…