Set Theoretic Adaptive filtering: Using periodogram and projections onto convex sets

In this paper we propose a novel adaptive filtering algorithm. Using the Set Theoretic Estimation framework, the algorithm exploits the information given by the power spectral density of the noise extracted from the periodogram of filtering error. With this information new appropriate sets are built and projections onto them are computed. The simulations results show that the algorithm has excellent convergence properties.