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Estimation of The Frequency of Very Short Signals by Involving Artificial Neural Networks.

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Title: Estimation of The Frequency of Very Short Signals by Involving Artificial Neural Networks.
Authors: BURTEA, Daniela Georgiana1, daniela.burtea@ubbcluj.ro, GILLICH, Edwald-Viktor2, edwald.gillich@ubbcluj.ro, TUFISI, Cristian2, cristian.tufisi@ubbcluj.ro, TUDOR, Luca3, luca.tudor@ubbcluj.ro
Source: Romanian Journal of Acoustics & Vibration; 2023, Vol. 20 Issue 2, p157-161, 5p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
An: 174926283
AccessLevel: 2
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Estimation of The Frequency of Very Short Signals by Involving Artificial Neural Networks.
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  Data: <searchLink fieldCode="JN" term="%22Romanian+Journal+of+Acoustics+%26+Vibration%22">Romanian Journal of Acoustics & Vibration</searchLink>; 2023, Vol. 20 Issue 2, p157-161, 5p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=174926283
RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 5
        StartPage: 157
    Titles:
      – TitleFull: Estimation of The Frequency of Very Short Signals by Involving Artificial Neural Networks.
        Type: main
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      – PersonEntity:
          Name:
            NameFull: BURTEA, Daniela Georgiana
      – PersonEntity:
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            NameFull: GILLICH, Edwald-Viktor
      – PersonEntity:
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            NameFull: TUFISI, Cristian
      – PersonEntity:
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            NameFull: TUDOR, Luca
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          Dates:
            – D: 01
              M: 07
              Text: 2023
              Type: published
              Y: 2023
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              Value: 15847284
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              Value: 20
            – Type: issue
              Value: 2
          Titles:
            – TitleFull: Romanian Journal of Acoustics & Vibration
              Type: main
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