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arXiv Machine Learning By Chenyu Zhu, Zeyang Li, Ziyi Xie, Jie Zhang

Few-Shot Specific Emitter Identification via Integrated Complex Variational Mode Decomposition and Spatial Attention Transfer

Read the original on arXiv Machine Learning →

The paper presents a new approach for specific emitter identification (SEI) that combines an integrated complex variational mode decomposition algorithm with a temporal convolutional network and a spatial attention mechanism. This method improves feature extraction from complex-valued signals and adaptively emphasizes informative segments, leading to higher identification accuracy. Experiments show the model reaches 96% accuracy using only 10 symbols and no prior knowledge, demonstrating its effectiveness in low‑data scenarios.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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