Wasserstein Stationary Subspace Analysis
Wasserstein Stationary Subspace Analysis is a scholarly work by Klaus-Robert Müller, published in 2018 in ''IEEE Journal on Selected Topics in Signal Processing''. The main subjects of the publication include interfacing, divergence, independent component analysis, mathematics, data mining, artificial intelligence, computer science, biological robustness, brain–computer interface, subspace topology, pattern recognition, and algorithm. The authors show the usefulness of the authors' novel algorithms for toy data demonstrating their mathematical properties and for real-world data (1) allowing better segmentation of time series and (2) brain-computer interfacing, where the Wasserstein-based measure of non-stationarity is used for spatial filter regularization and gives rise to higher decoding performance.