Yet another subspace tracker

The paper introduces a new algorithm for tracking the dominant subspace of the correlation matrix associated with time series. This algorithm greatly outperforms many well-known subspace trackers in terms of subspace estimation. Moreover, it guarantees the orthonormality of the subspace weighting matrix at each iteration, and reaches the lowest complexity found in the literature.