Adaptive RLS filtering under the cyclo-stationary regime

We present a methodology for adaptive filtering and system identification under the cyclostationary regime. Our technique is based on a deterministic periodic least-squares criterion, and gives rise to adaptive periodic recursive-least-squares (P-RLS) algorithms. Furthermore, we show that every adaptive RLS algorithm has a P-RLS counterpart, which has exactly the same architecture and the same performance attributes, and differs only in the length of the delay used in its time-update recursions