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Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel.

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Title: Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel.
Authors: Kumar, Arun1, Gaur, Nishant2, Nanthaamornphong, Aziz3, aziz.n@phuket.psu.ac.th, Tani, Andrea
Source: Journal of Electrical & Computer Engineering; 3/3/2025, Vol. 2025, p1-15, 15p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 183918473
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Electrical+%26+Computer+Engineering%22">Journal of Electrical & Computer Engineering</searchLink>; 3/3/2025, Vol. 2025, p1-15, 15p
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1155/jece/9506922
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 15
        StartPage: 1
    Titles:
      – TitleFull: Hybrid Spectrum Sensing Using Neural Network–Based MF and ED for Enhanced Detection in Rayleigh Channel.
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            NameFull: Kumar, Arun
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            NameFull: Gaur, Nishant
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            NameFull: Nanthaamornphong, Aziz
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            NameFull: Tani, Andrea
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            – D: 03
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              Text: 3/3/2025
              Type: published
              Y: 2025
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              Value: 20900147
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              Value: 2025
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            – TitleFull: Journal of Electrical & Computer Engineering
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