Search Results - "Zhou, Huaji"

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  1. 1

    Spectrum sensing based on deep learning classification for cognitive radios by Zheng, Shilian, Chen, Shichuan, Qi, Peihan, Zhou, Huaji, Yang, Xiaoniu

    Published in China communications (01-02-2020)
    “…Spectrum sensing is a key technology for cognitive radios. We present spectrum sensing as a classification problem and propose a sensing method based on deep…”
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    Journal Article
  2. 2

    A Synthetic Aperture Radar Imaging Simulation Method for Sea Surface Scenes Combined with Electromagnetic Scattering Characteristics by He, Yao, Xu, Le, Huo, Jincong, Zhou, Huaji, Shi, Xiaowei

    Published in Remote sensing (Basel, Switzerland) (01-09-2024)
    “…Synthetic aperture radar (SAR) simulation is a vital tool for planning SAR missions, interpreting SAR images, and extracting valuable information. SAR imaging…”
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    Journal Article
  3. 3

    Generative adversarial network-based electromagnetic signal classification: A semi-supervised learning framework by Zhou, Huaji, Jiao, Licheng, Zheng, Shilian, Yang, Lifeng, Shen, Weiguo, Yang, Xiaoniu

    Published in China communications (01-10-2020)
    “…Generative adversarial network (GAN) has achieved great success in many fields such as computer vision, speech processing, and natural language processing,…”
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    Journal Article
  4. 4

    Deep spectrum prediction in high frequency communication based on temporal-spectral residual network by Yu, Ling, Chen, Jin, Zhang, Yuming, Zhou, Huaji, Sun, Jiachen

    Published in China communications (01-09-2018)
    “…High frequency (HF) communication is widely spread due to some merits like easy deployment and wide communication coverage. Spectrum prediction is a promising…”
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    Journal Article
  5. 5

    Electromagnetic Signal Classification Based on Class Exemplar Selection and Multi-Objective Linear Programming by Zhou, Huaji, Bai, Jing, Niu, Linchun, Xu, Jie, Xiao, Zhu, Zheng, Shilian, Jiao, Licheng, Yang, Xiaoniu

    Published in Remote sensing (Basel, Switzerland) (01-03-2022)
    “…In the increasingly complex electromagnetic environment, a variety of new signal types are appearing; however, existing electromagnetic signal classification…”
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    Journal Article
  6. 6

    Deep radio signal clustering with interpretability analysis based on saliency map by Zhou, Huaji, Bai, Jing, Wang, Yiran, Ren, Junjie, Yang, Xiaoniu, Jiao, Licheng

    Published in Digital communications and networks (01-10-2024)
    “…With the development of information technology, radio communication technology has made rapid progress. Many radio signals that have appeared in space are…”
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    Journal Article
  7. 7

    Primary user adversarial attacks on deep learning-based spectrum sensing and the defense method by Zheng, Shilian, Ye, Linhui, Wang, Xuanye, Chen, Jinyin, Zhou, Huaji, Lou, Caiyi, Zhao, Zhijin, Yang, Xiaoniu

    Published in China communications (01-12-2021)
    “…The spectrum sensing model based on deep learning has achieved satisfying detection performence, but its robustness has not been verified. In this paper, we…”
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    Journal Article
  8. 8

    Weight-Variable Scattering Convolution Networks and Its Application in Electromagnetic Signal Classification by Zhou, Huaji, Jiao, Licheng, Zheng, Shilian, Chen, Shichuan, Yang, Lifeng, Shen, Weiguo, Yang, Xiaoniu

    Published in IEEE access (2019)
    “…Deep learning is an important support for the development of cognitive communication in the cognitive Internet of Things (IoT). Deep convolution neural…”
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    Journal Article
  9. 9

    Percutaneous snare-retrieval of intracardiac thrombus under fluoroscopic and transesophageal echocardiography guidance: case report and systematic review by Zhou, Huaji, Wang, Bing, Pan, Jun, Qiu, Chenyang, Yu, Xinyu, He, Yangyan, Zhu, Qianqian, Yu, Lei, Wu, Ziheng, Li, Donglin, Zhang, Hongkun

    Published in Frontiers in cardiovascular medicine (09-05-2023)
    “…Intracardiac foreign bodies (IFB) are rare clinical conditions. There are now several reports on the percutaneous retrieval of IFB under fluoroscopy. However,…”
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    Journal Article
  10. 10

    An electromagnetic signal classification method inspired by the visual characteristics of biological dual-channel by Dai, Shaogang, Zhou, Huaji

    Published in Wireless networks (01-02-2024)
    “…Automatic modulation classification of electromagnetic signals has an important role in the field of civil and military signal processing, its researches are…”
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    Journal Article
  11. 11

    SR2CNN: Zero-Shot Learning for Signal Recognition by Dong, Yihong, Jiang, Xiaohan, Zhou, Huaji, Lin, Yun, Shi, Qingjiang

    “…Signal recognition is one of the significant and challenging tasks in the signal processing and communications field. It is often a common situation that…”
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    Journal Article
  12. 12

    A New Method for Joint Sparse DOA Estimation by Hou, Jinyong, Wang, Changlong, Zhao, Zixuan, Zhou, Feng, Zhou, Huaji

    Published in Sensors (Basel, Switzerland) (12-11-2024)
    “…To tackle the issue of poor accuracy in single-snapshot data processing for Direction of Arrival (DOA) estimation in passive radar systems, this paper…”
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    Journal Article
  13. 13

    Energy-Constrained Completion Time Minimization in UAV-Enabled Internet of Things by Gu, Jiangchun, Wang, Haichao, Ding, Guoru, Xu, Yitao, Xue, Zhen, Zhou, Huaji

    Published in IEEE internet of things journal (01-06-2020)
    “…Unmanned-aerial-vehicles (UAVs)-enabled wireless communication for Internet-of-Things (IoT) applications has attracted increasing attention. This article…”
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    Journal Article
  14. 14

    MsmcNet: A Modular Few-Shot Learning Framework for Signal Modulation Classification by Wang, Yiran, Bai, Jing, Xiao, Zhu, Zhou, Huaji, Jiao, Licheng

    “…With the development of deep learning (DL) technology, the feature extraction capability of networks has gradually been enhanced, and high accuracy has been…”
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    Journal Article
  15. 15

    SigDA: A Superimposed Domain Adaptation Framework for Automatic Modulation Classification by Wang, Shuang, Xing, Hantong, Wang, Chenxu, Zhou, Huaji, Hou, Biao, Jiao, Licheng

    “…Due to the uncertainty of non-cooperative communication channels, the received signals often contain various impairment factors, leading to a significant…”
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    Journal Article
  16. 16

    Class Incremental Learning With Few-Shots Based on Linear Programming for Hyperspectral Image Classification by Bai, Jing, Yuan, Anran, Xiao, Zhu, Zhou, Huaji, Wang, Dingchen, Jiang, Hongbo, Jiao, Licheng

    Published in IEEE transactions on cybernetics (01-06-2022)
    “…Hyperspectral imaging (HSI) classification has drawn tremendous attention in the field of Earth observation. In the big data era, explosive growth has occurred…”
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    Journal Article
  17. 17

    A Deep Learning-Based Intelligent Receiver for Improving the Reliability of the MIMO Wireless Communication System by Wang, Bin, Xu, Ke, Zheng, Shilian, Zhou, Huaji, Liu, Yang

    Published in IEEE transactions on reliability (01-06-2022)
    “…Multiple-input-multiple-output (MIMO) technology is one of the most widely used communication technologies. However, with the increasing number of antennas,…”
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    Journal Article
  18. 18

    An Interpretable Explanation Approach for Signal Modulation Classification by Bai, Jing, Lian, Yuheng, Wang, Yiran, Ren, Junjie, Xiao, Zhu, Zhou, Huaji, Jiao, Licheng

    “…Signal modulation classification (SMC) has attracted extensive attention for its wide application in the military and civil fields. The current direction of…”
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    Journal Article
  19. 19

    Toward the Intelligent OFDM Receiving Method With Hybrid Knowledge and Data Driven in IoT by Wang, Bin, Dai, Hui, Zhou, Huaji, Yuan, Zhuang

    Published in IEEE internet of things journal (15-05-2024)
    “…Orthogonal frequency-division multiplexing (OFDM) is regarded as one of the key technologies in wireless communications, particularly in the integration of…”
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    Journal Article
  20. 20

    Multi-dimensional spectrum map construction: A tensor perspective by Mengyun Tang, Guoru Ding, Zhen Xue, Jing Zhang, Huaji Zhou

    “…Spectrum data, which is usually characterized by many dimensions, such as location, frequency, time and signal strength, presents formidable challenges in…”
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    Conference Proceeding