New spatially constrained source separation using tensor decomposition

In this paper common spatial patterns filter has been combined with conventional PARAFAC2 tensor decomposition in the design of a new spatially constrained source separation system. This approach is particularly useful in separation of weak intermittent signal components such as interictal discharges originated from deep brain sources. The results of applying the method to synthetic data show that it outperforms conventional blind source separation methods which are often unable to separate weak intermittent nonstationary sources.