arXiv:2607. 08031v1 Announce Type: cross Abstract: The dynamics of communication environments induce significant distribution shifts across domains, challenging the generalization of deep learning-based automatic modulation classification (AMC) models.
By Shuang Wang, Chenxu Wang, Hantong Xing, Hanlin Mo, Lirong Han, Licheng Jiao
arXiv:2606. 00081v1 Announce Type: cross Abstract: Distributed Acoustic Sensing (DAS) enables large-scale monitoring through optical fibers, but its high dimensionality and complex spatio-temporal patterns make event classification demanding.
By Michel Dione (CERI SN - IMT Nord Europe), Jerry Lonlac (CERI SN - IMT Nord Europe), H\'el\`ene Louis (CERI SN - IMT Nord Europe), Anthony Fleury (CERI SN - IMT Nord Europe), Stephane Lecoeuche
arXiv:2608. 00796v1 Announce Type: cross Abstract: Automatic RF modulation recognition is of critical importance in spectrum monitoring, electronic warfare, and cognitive radio applications, where low signal-to-noise ratio (SNR) conditions and the growing diversity of modulation schemes limit the performance of existing methods.
By Nurettin Safak, Durdu Can Yerdeyatar, Muhammet Sefa Demirel, Alperen Marasli, Taha Eren Atmaca, Ozgun Ersoy
arXiv:2507. 12645v1 Announce Type: cross Abstract: The increasing need for accurate and unified analysis of diverse biological signals, such as ECG and EEG, is paramount for comprehensive patient assessment, especially in synchronous monitoring.
By Mohammed Guhdar, Ramadhan J. Mstafa, Abdulhakeem O. Mohammed
arXiv:2606. 24075v1 Announce Type: cross Abstract: Although deep learning-based methods can achieve high accuracy in automatic modulation recognition (AMR) tasks, their high computational cost makes it difficult to strike a balance between accuracy and power consumption, thereby limiting their application on resource-constrained platforms.
By Xiaohu Li, Chongxiao Qu, Caiyong Lin, Chenxiao Dou, Wei Hua
arXiv:2601. 22580v2 Announce Type: replace-cross Abstract: The success of Large Language Models (LLMs) hinges on the stable training of deep Transformer architectures.
By Chao Wang, Bei Li, Jiaqi Zhang, Xinyu Liu, Yuchun Fan, Linkun Lyu, Xin Chen, Jingang Wang, Tong Xiao, Peng Pei, Xunliang Cai