A PDF Estimation-Based Blind Criterion for Adaptive Equalization

作者: Charles C. Cavalcante , F. Rodrigo , Cesar M. Mota , P. Cavalcanti

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

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