Improved Modulation Classification Based on Hough Transforms of Constellation Diagrams Using CNN for the UWA-OFDM Communication System

The Automatic Modulation Classification (AMC) for underwater acoustic signals enables more efficient utilization of the acoustic spectrum. Deep learning techniques significantly improve classification performance. Hence, they can be applied in AMC work to improve the underwater acoustic (UWA) commun...

書誌詳細
出版年:	Eng
主要な著者:	Mohamed A. Abdel-Moneim, Mohamed K. M. Gerwash, El-Sayed M. El-Rabaie, Fathi E. Abd El-Samie, Khalil F. Ramadan, Nariman Abdel-Salam
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2025-06-01
主題:	automatic modulation classification (AMC) underwater acoustic (UWA) communications Hough transform (HT) convolutional neural network (CNN)
オンライン･アクセス:	https://www.mdpi.com/2673-4117/6/6/127

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