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Adaptive Blind Deconvolution of Linear Channels Using Renyi's Entropy with Parzen Window Estimation
2004
IEEE Transactions on Signal Processing
Blind deconvolution of linear channels is a fundamental signal processing problem that has immediate extensions to multiple-channel applications. In this paper, we investigate the suitability of a class of Parzen-window-based entropy estimates, namely Renyi's entropy, as a criterion for blind deconvolution of linear channels. Comparisons between maximum and minimum entropy approaches, as well as the effect of entropy order, equalizer length, sample size, and measurement noise on performance,
doi:10.1109/tsp.2004.827202
fatcat:d5figwihxjbzte5rciipyt7chm