Foreground Removal using FastICA: A Showcase of LOFAR-EoR
  We introduce a new implementation of the FastICA algorithm on simulated LOFAR
EoR data with the aim of accurately removing the foregrounds and extracting the
21-cm reionization signal. We find that the method successfully removes the
foregrounds with an average fitting error of 0.5 per cent and that the 2D and
3D power spectra are recovered across the frequency range. We find that for
scales above several PSF scales the 21-cm variance is successfully recovered
though there is evidence of noise leakage into the reconstructed foreground
components. We find that this blind independent component analysis technique
provides encouraging results without the danger of prior foreground
assumptions.
