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检索条件"主题词=Automatic Modulation Classification"
373 条 记 录,以下是81-90 订阅
排序:
AMCRN: Few-Shot Learning for automatic modulation classification
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IEEE COMMUNICATIONS LETTERS 2022年 第3期26卷 542-546页
作者: Zhou, Quan Zhang, Ronghui Mu, Junsheng Zhang, Hongming Zhang, Fangpei Jing, Xiaojun Beijing Univ Posts & Telecommun Key Lab Trustworthy Distributed Comp & Serv Beijing 100876 Peoples R China China Elect Technol Grp Corp Informat Sci Acad Beijing 100048 Peoples R China
Deep learning (DL) has been widely applied in automatic modulation classification (AMC), while the superb performance highly depends on high-quality datasets. Motivated by this, the AMC under few-shot conditions is co... 详细信息
来源: 评论
A Deep Learning-Based Novel Class Discovery Approach for automatic modulation classification
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IEEE COMMUNICATIONS LETTERS 2023年 第11期27卷 3018-3022页
作者: Zhang, Rui Zhao, Yanlong Yin, Zhendong Li, Dasen Wu, Zhilu Harbin Inst Technol Sch Elect & Informat Engn Harbin 150001 Peoples R China
The existing automatic modulation classification (AMC) methods require the training and testing datasets share a common set of modulation categories. However, the AMC model may encounter the need to discriminate novel... 详细信息
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ConvLSTMAE: A Spatiotemporal Parallel Autoencoders for automatic modulation classification
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IEEE COMMUNICATIONS LETTERS 2022年 第8期26卷 1804-1808页
作者: Shi Yunhao Xu Hua Jiang Lei Qi Zisen Air Force Engn Univ Informat & Nav Coll Xian 710038 Shaanxi Peoples R China
automatic modulation classification (AMC) is the key technique in both military and civilian wireless communication. However, the performance is unsatisfactory, even several deep learning-based methods are involved. T... 详细信息
来源: 评论
RanNet: Learning Residual-Attention Structure in CNNs for automatic modulation classification
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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年 第6期11卷 1243-1247页
作者: Huynh-The, Thien Pham, Quoc-Viet Nguyen, Toan-Van Nguyen, Thanh Thi da Costa, Daniel Benevides Kim, Dong-Seong Kumoh Natl Inst Technol ICT Convergence Res Ctr Gumi 39177 South Korea Kumoh Natl Inst Technol Dept IT Convergence Gumi 39177 South Korea Pusan Natl Univ Korean Southeast Ctr Ind Revolut Leader Educ 4 Busan South Korea Utah State Univ Dept Elect & Comp Engn Logan UT 84322 USA Deakin Univ Sch Informat Technol Waurn Ponds Vic 3216 Australia Technol Innovat Inst AI & Telecom Res Ctr Abu Dhabi U Arab Emirates Natl Yunlin Univ Sci & Technol Future Technol Res Ctr Touliu 64002 Yunlin Taiwan
With the rapid emergence of advanced technologies for wireless communications, automatic modulation classification (AMC) has been deployed in the physical layer to blindly identify the modulation fashion of an incomin... 详细信息
来源: 评论
Channel-Robust automatic modulation classification Using Companding Spectral Quotient Cumulants
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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2024年 第11期73卷 17749-17753页
作者: Huang, Sai Chen, Yuting He, Jiashuo Chang, Shuo Feng, Zhiyong Beijing Univ Posts & T elecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China
automatic modulation classification (AMC) is to identify the modulation format of the received signal corrupted by the channel effects and noise. Most existing works focus on the impact of noise while relatively littl... 详细信息
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MAMCOptimal on Accuracy and Efficiency for automatic modulation classification With Extended Signal Length
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IEEE COMMUNICATIONS LETTERS 2024年 第12期28卷 2864-2868页
作者: Zhang, Yezhuo Zhou, Zinan Cao, Yichao Li, Guangyu Li, Xuanpeng Southeast Univ Sch Instrument Sci & Engn Nanjing 210096 Jiangsu Peoples R China Univ Sci & Technol Sch Comp Sci & Engn Nanjing 210094 Jiangsu Peoples R China
In automatic modulation classification (AMC), extended signal lengths offer a bounty of information, yet impede the model's adaptability, introduce more noise interference, extend the training and inference time, ... 详细信息
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Multi-Scale Feature Fusion and Distribution Similarity Network for Few-Shot automatic modulation classification
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IEEE SIGNAL PROCESSING LETTERS 2024年 31卷 2890-2894页
作者: Tan, Haoyue Zhang, Zhenxi Li, Yu Shi, Xiaoran Zhou, Feng Xidian Univ Xian 710126 Peoples R China
automatic modulation classification (AMC), as a key technology of cognitive radio, has become a focal point of research. However, most deep learning-based AMC methods require an extensive number of labeled signals to ... 详细信息
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A Fast Multi-Loss Learning Deep Neural Network for automatic modulation classification
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IEEE TRANSACTIONS ON COGNITIVE COMMUNICATIONS AND NETWORKING 2023年 第6期9卷 1503-1518页
作者: Chang, Shuo Yang, Zheng He, Jiashuo Li, Rong Huang, Sai Feng, Zhiyong Beijing Univ Posts & Telecommun Sch Cyberspace Secur Beijing 100876 Peoples R China Beijing Univ Posts & Telecommun Key Lab Universal Wireless Commun Minist Educ Beijing 100876 Peoples R China State Radio Monitoring Ctr Beijing Radio Monitoring Stn Beijing 100876 Peoples R China
automatic modulation classification (AMC) enables significant applications in both the military and civilian domains. Inspired by the great success of deep learning (DL), a dual-stream neural network using in-phase/qu... 详细信息
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On classifiers for blind feature-based automatic modulation classification over multiple-input-multiple-output channels
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IET COMMUNICATIONS 2016年 第7期10卷 790-795页
作者: Kharbech, Sofiane Dayoub, Iyad Zwingelstein-Colin, Marie Simon, Eric Pierre Higher Inst Technol Studies Gabes Dept Commun & Informat Technol STIC Gabes 6011 Tunisia Univ Valenciennes & Hainaut Cambresis IEMN DOAE Lab UMR CNRS 8520 F-59313 Valenciennes France Univ Lille 1 TELICE Lab IEMN UMR CNRS 8520 F-59100 Lille France
modulation recognition is crucial for a good environmental awareness required by cognitive radio systems. In this study, the authors design and compare models of four among the most commonly used classifiers for featu... 详细信息
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Dyadic Aggregated Autoregressive Model (DASAR) for automatic modulation classification
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IEEE ACCESS 2020年 8卷 156096-156103页
作者: Pinto-Orellana, Marco Antonio Hammer, Hugo Lewi Oslo Metropolitan Univ Fac Technol Art & Design Dept Mech Elect & Chem Engn N-0103 Oslo Norway Oslo Metropolitan Univ Fac Technol Art & Design Dept Informat Technol N-0103 Oslo Norway Oslo Metropolitan Univ Simula Metropolitan Ctr N-0103 Oslo Norway
In this article, we presented a novel spectral estimation method, the dyadic aggregated autoregressive model (DASAR), that characterizes the spectrum dynamics of a modulated signal. DASAR enhances automatic modulation... 详细信息
来源: 评论