Independent component analysis (ICA) is a rapidly emerging technology in the field of advanced signal processing. It separates a set of observed signals into the statistically most independent components by appealing to higher-order statistics. ICA retrieves the original source signals if the observations are actually a mixture of superposed signals that are statistical independent. No a priori information is required about waveforms or polarisations of the desired source signals. <br><br>ICA can be used to separate P- and S-waves in 3-component seismic reflection data without knowledge of P- and S-wave near-surface velocities or density. Wavefield separation is achieved by exploiting statistical differences between P- and S-waves only. The ICA wavefield separation technique is exact in a laterally inhomogeneous anisotropic Earth with a homogeneous anisotropic near-surface layer if only upgoing waves are present.


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