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Intra-pulse modulation classification of radar emitter signals is beneficial in analyzing radar systems. Recently, convolutional neural networks (CNNs) have been used in classification of intra-pulse modulation of radar emitter signals, and the results proved better than the traditional methods. However, there is a key disadvantage in these CNN-based methods: the CNN requires enough labeled samples. Labeling the modulations of radar emitter signal samples requires a tremendous amount of priordoi:10.3390/rs14092059 fatcat:lzfesbpkvradjjrl6sxmngpali