The goal of this paper is to present a theoretical and practical introduction to generalized
eigendecomposition (GED), which is a robust and flexible framework used for dimension
reduction and source separation in multichannel signal processing. In cognitive
electrophysiology, GED is used to create spatial filters that maximize a researcher-specified
contrast. For example, one may wish to exploit an assumption that different sources have
different frequency content, or that sources vary in magnitude across experimental …