Approximated power iterations for fast subspace tracking

This paper introduces a fast implementation of the power iterations method for subspace tracking, based on an approximation less restrictive than the well-known projection approximation. This algorithm guarantees the orthonormality of the estimated subspace-weighting matrix at each iteration, and satisfies a global and exponential convergence property. Moreover, it outperforms many subspace trackers related to the power method, such as PAST. NIC, NP3 and OPAST, while keeping the same computational complexity.