• Journal of Terahertz Science and Electronic Information Technology
  • Vol. 20, Issue 1, 8 (2022)
LI Shuang1、*, LIU Haipeng2, and GUO Lantu3
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • 3[in Chinese]
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    DOI: 10.11805/tkyda2021168 Cite this Article
    LI Shuang, LIU Haipeng, GUO Lantu. Information mining and association analysis based on electromagnetic environment data[J]. Journal of Terahertz Science and Electronic Information Technology , 2022, 20(1): 8 Copy Citation Text show less

    Abstract

    With the development of urban communication technology and the increase of frequency equipment, the electromagnetic environment becomes more and more complex. Fully understanding the characteristics of spectrum resource utilization in the past is the key to improve the efficiency of spectrum management. A complete process about detailed data quality analysis for big data in complex and diverse electromagnetic environment is proposed, in order to explore the characteristics of spectrum utilization more comprehensively. The spectrum correlation for different channels in the same service, and for different channels in different services, is performed. Attribute construction is carried out for big data of electromagnetic environment, including the attributes of frequency dimension occupancy and time dimension occupancy. The multi-dimensional Gaussian mixture model in the field of image processing is introduced to remove the background noise of the electromagnetic signal and extract the electromagnetic signal, which can lay the foundation for the subsequent information mining and association analysis.
    LI Shuang, LIU Haipeng, GUO Lantu. Information mining and association analysis based on electromagnetic environment data[J]. Journal of Terahertz Science and Electronic Information Technology , 2022, 20(1): 8
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