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Kurtosis minimization has been applied for the existing blind equalization schemes but the corresponding optimization procedures are very sensitive to the channel conditions and the initial conditions. In this paper, we introduce a new cognitive receiver front-end, which includes a novel switching blind equalizer and an automatic modulation classifier. We design a switching criterion based on the kurtosis/normalized moment ratio threshold to select the better signal between the raw data and the equalized sequence. Simulations demonstrate that our proposed robust switching blind equalization scheme can significantly outperform the existing blind equalizer and would not degrade the subsequent modulation classification accuracy.