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In this paper, it is demonstrated that decision feedback equalization (DFE) based on soft-decisions is able to outperform hard-decision DFE, with an attractive computational cost that is polynomial in the number of symbols to be recovered. A group of soft-decision feedback equalizers (SDFE) with probabilistic data association are developed for multi-input multi-output (MIMO) wireless communication systems operating in time dispersive channels. Block transmissions with zero-padded precoding are employed to guarantee channel identifiability. Computer simulations indicate that SDFE offers close-to-optimal error probability performance without incurring exponential complexity. Further improvements on these SDFE schemes promise enhanced performance at a reduced computational cost.