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In this paper, we address the problem of unsupervised (blind) space-time equalization of frequency-selective multiple-input multiple-output (MIMO) channels. The motivation behind this work is that in order to provide the high transmission rates that data-demanding applications require, wireless multiple antenna (MIMO) systems will have to operate in wide bandwidths. In such scenarios, frequency selectivity may induce important intersymbol interference (ISI), in addition to the interuser interference (IUI) that each antenna's transmitted stream of data suffers from the other antennas. Under these conditions, channel estimation of the frequency-selective MIMO channel may become a daunting task that ultimately reduces the effective transmission rate. We present a family of globally convergent blind space-time equalization techniques, developed from multiuser kurtosis output-based criteria, which allow the recovery of the MIMO channel inputs without the training overhead that channel estimation typically requires, thus improving the MIMO channel's spectral efficiency.