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Modulation recognition is an important issue in cognitive radio research area, however, high recognition precision is usually achieved by relative large number of training data and more various features of digital signal, which call for much more resource. In this paper, a novel modulation recognition approach is proposed, 4th order cyclic cumulants vectors of digital signal is applied for modulation recognition, which are constructed as features to train support vector machine classifiers fordoi:10.12783/dtcse/aice-ncs2016/5690 fatcat:mbiy36qumbhcpgs5qlaym4ysb4