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20212026
most citedA Radar Signal Deinterleaving Method Based on Semantic Segmentation with Neural Network

64 citations · 71 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SP2026

Compositional Zero-Shot Recognition based on Tangent Space Disentanglement for Composite Modulation Signals

Yurui Zhao, Xiang Wang, Zhitao Huang +1

Automatic composite modulation recognition (ACMR) is critical for integrated sensing and communication (ISAC) systems, while conventional approaches face significant challenges due…

cs.LG2026

Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis

Yurui Zhao, Xiang Wang, Jingreng Lei +3

Designing effective feature extractors is critical for blind signal analysis tasks such as automatic modulation recognition (AMR), signal scheme recognition (SSR), and \color{black…

eess.SP2024

Conformal Shield: A Novel Adversarial Attack Detection Framework for Automatic Modulation Classification

Tailai Wen, Da Ke, Xiang Wang +1

Deep learning algorithms have become an essential component in the field of cognitive radio, especially playing a pivotal role in automatic modulation classification. However, Deep…

eess.SP2022★ 7 cited

A New Radar Signal Multiparameter-Based Deinterleaving Method

Wang Chao, Liu Weisong, Li Xueqiong +2

Radar signal deinterleaving has been extensively and thoroughly investigated in the electronic reconnaissance field. In this work, a new radar signal multiparameter-based deinterle…

eess.SP2021★ 64 cited

A Radar Signal Deinterleaving Method Based on Semantic Segmentation with Neural Network

Wang Chao, Sun Liting, Liu Zhangmeng +1

Radar signal deinterleaving is an important part of electronic reconnaissance. This study proposes a new radar signal deinterleaving method based on semantic segmentation, which we…