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Titlebook: Communications, Signal Processing, and Systems; Proceedings of the 1 Qilian Liang,Wei Wang,Baoju Zhang Conference proceedings 2023 The Edit

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31#
發(fā)表于 2025-3-26 22:29:47 | 只看該作者
1876-1100 gration of algorithms, hardware, software, and systems.This book brings together papers presented at the 2021 International Conference on Communications, Signal Processing, and Systems,?Changbaishan, China, July 23-24, 2022,?which provides a venue to disseminate the latest developments and to discus
32#
發(fā)表于 2025-3-27 03:55:09 | 只看該作者
33#
發(fā)表于 2025-3-27 09:05:57 | 只看該作者
34#
發(fā)表于 2025-3-27 11:08:31 | 只看該作者
35#
發(fā)表于 2025-3-27 17:04:56 | 只看該作者
,Directional Modulation Design Based on?Hybrid Beamforming Structure for?Massive MIMO,analog beamforming structure is widely adopted. In this paper, the DM design problem is studied based on such a hybrid implementation for the first time. As a representative example, the interleaved subarrays are used for the proposed design. Design examples are provided to show the effectiveness of the proposed design.
36#
發(fā)表于 2025-3-27 20:33:28 | 只看該作者
37#
發(fā)表于 2025-3-27 23:18:36 | 只看該作者
https://doi.org/10.1007/978-3-031-49155-9idge path extraction method based on synchrosqueezed transformation is used to separate the components in time-frequency domain. Experimental results show that the proposed method achieves high accuracy in extracting component micro-Doppler features and recognizing UAV information.
38#
發(fā)表于 2025-3-28 03:28:46 | 只看該作者
39#
發(fā)表于 2025-3-28 08:04:07 | 只看該作者
H. P. Garg,S. C. Mullick,A. K. Bhargavathe model under each algorithm, and the data set was validated using cross-validation. The results showed that the models trained with random forest could classify the “set” and “adjustment” labels with clinical applicability.
40#
發(fā)表于 2025-3-28 13:59:53 | 只看該作者
,Micro-doppler Feature Extraction of?UAVs Based on?Synchrosqueezed Transform and?Ridge Path Regroupiidge path extraction method based on synchrosqueezed transformation is used to separate the components in time-frequency domain. Experimental results show that the proposed method achieves high accuracy in extracting component micro-Doppler features and recognizing UAV information.
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