  We propose an online tensor subspace tracking algorithm based on the CP
decomposition exploiting the recursive least squares (RLS), dubbed OnLine
Low-rank Subspace tracking by TEnsor CP Decomposition (OLSTEC). Numerical
evaluations show that the proposed OLSTEC algorithm gives faster convergence
per iteration comparing with the state-of-the-art online algorithms.
