Robust versions of the PAST algorithm

In this contribution we analyze the Projection Approximation Subspace Tracking (PAST) algorithm by a novel analysis method based on Singular Value Decomposition (SVD). Based on the gained new insights we propose several robust algorithmic modifications that allow to guarantee stability of the algorithm run for normalized step-sizes. Furthermore we investigate the tracking behavior for such step-size choices.