A PDF Estimation-Based Blind Criterion for Adaptive Equalization

"A blind criterion for adaptive equalization based on probability density function (pdf) estimation is proposed. The criterion measures the divergence between the pdf of an ideally equalized signal and the one from a parametric model resulting in a cost function that is a sort of entropy minimization of the equalizer output signal. It is also shown a link between the constant modulus (CM) criterion and the proposed one under certain circumstances. Some convergence properties are studied and the performance of the proposal is evaluated through simulations faced to a classical blind criterion."