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Robust Wiener filtering has previously been considered for the single-input (scalar) case where there is no channel distortion and where the signal to be estimated is the source signal itself. Here, these results are extended to the multiple-input (vector) case where linear channel distortion is allowed and the signal to be estimated is a linear-filtered version of the source signal. The results are obtained from those for the single-input ease by modifying the constraints on signal and noise characteristics. Such a modification is motivated by examining the expression of the mean-squared error for the optimum filter.