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Aiming at the problem of low recognition accuracy caused by insufficient labeled signal samples in communication emitter identification technology, a semi-supervised deep learning method for emitter identification based on pseudo label is proposed. This method uses the idea of weighted average to improve the assignment method of pseudo label, effectively enhances the quality of pseudo label, and improves the robustness of network model. This paper introduces how to design a semi-supervised deep learning method based on the idea of pseudo label, and explains the effectiveness of pseudo label theoretically by using the concept of entropy regularization algorithm. Convolutional neural network is designed for signal samples, Taking different number of labeled samples and unlabeled samples as training set, the recognition accuracy of the improved pseudo label semi-supervised method in the test set is obtained. The results show that the method has better recognition effect and stronger superiority than the full supervised method and the original pseudo label semi-supervised method.