The USC Andrew and Erna Viterbi School of Engineering USC Signal and Image Processing Institute USC Ming Hsieh Department of Electrical and Computer Engineering University of Southern California

Technical Report USC-SIPI-253

“Maximum A Posteriori Filter Estimation for Cauchy Data Using Lower-Order Statistics”

by Russell H. Lambert and Chrysostomos L. Nikias

March 1994

A Maximum A Posteriori (MAP) estimation approach is used to determine the multipath channel parameters of a system driven with Cauchy data. This is a blind deconvolution problem with the input driving sequence having a Cauchy probability density function. The fact that the Cauchy distribution is not Bussgang, and has infinite variance, requires the development of a new blind deconvolution formulation which estimates the forward filter, instead of the inverse filter as in traditional deconvolution schemes.

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