On the Relationships between MMSE and Information-Theoretic-Based Blind Criterion for Minimum BER Filtering

Authors:
Charles Casimiro Cavalcante;João M. Romano
Affiliations:
GTEL, DETI, Federal University of Ceará, Brazil;DSPCom, FEEC, University of Campinas, Brazil
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

In this paper we present a relationship between supervised (MMSE) and unsupervised criteria for minimum bit error rate (BER) filtering. A criterion based on the probability density function (pdf) estimation which has an information theoretical approach is used to link the MMSE criterion and the maximum a posteriori one in order to obtain a linear filter that minimizes the BER. An analytical relationship among those three criteria is presented and analyzed showing the limits imposed to achieve minimum BER without training sequences when the pdf estimation-based criterion is considered.