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ABOUT THE ACCURACY OF ESTIMATED FREQUENCIES WITH THE PyFEST SOFTWARE.

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Title: ABOUT THE ACCURACY OF ESTIMATED FREQUENCIES WITH THE PyFEST SOFTWARE.
Authors: Gillich, Gilbert-Rainer1, Nedelcu, Dorian1, Iancu, Vasile1, Gillich, Nicoleta1
Source: Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie. 2019, Issue 4, p13-18. 6p.
Subjects: Python programming language, Algorithms, Computer software, Language ability testing
Abstract: This paper presents a method to estimate frequencies with high accuracy that is based on an iterative method. The method consists in applying rectangular windows with different lengths to the acquired or generated signal in order to control the resulted frequency resolution. For each truncated signal we calculate the Discrete Fourier Transform (DFT), finally being overlapped all achieved spectra. So, we obtain a unique spectrum form all DFTs, which have an extremely fine frequency resolution. For the three biggest amplitude values found in the vicinity of the targeted frequency we perform an interpolation and find the regression curve and the maximum of it. This represent the true amplitude of the signal's targeted harmonic component. The inter-bin position on which this amplitude is found indicates the true frequency. The algorithm is transposed in an application written in the Python programming language and tests are made to find the accuracy of the proposed estimation method. Since we find frequency estimates very close to the generated frequencies, the method and the application are successfully validated. [ABSTRACT FROM AUTHOR]
Copyright of Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie is the property of Universitatea Constantin Brancusi din Targu-Jiu and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: ABOUT THE ACCURACY OF ESTIMATED FREQUENCIES WITH THE PyFEST SOFTWARE.
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  Data: <searchLink fieldCode="JN" term="%22Annals+of+'Constantin+Brancusi'+University+of+Targu-Jiu%2E+Engineering+Series+%2F+Analele+Universităţii+Constantin+Brâncuşi+din+Târgu-Jiu%2E+Seria+Inginerie%22">Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie</searchLink>. 2019, Issue 4, p13-18. 6p.
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  Data: This paper presents a method to estimate frequencies with high accuracy that is based on an iterative method. The method consists in applying rectangular windows with different lengths to the acquired or generated signal in order to control the resulted frequency resolution. For each truncated signal we calculate the Discrete Fourier Transform (DFT), finally being overlapped all achieved spectra. So, we obtain a unique spectrum form all DFTs, which have an extremely fine frequency resolution. For the three biggest amplitude values found in the vicinity of the targeted frequency we perform an interpolation and find the regression curve and the maximum of it. This represent the true amplitude of the signal's targeted harmonic component. The inter-bin position on which this amplitude is found indicates the true frequency. The algorithm is transposed in an application written in the Python programming language and tests are made to find the accuracy of the proposed estimation method. Since we find frequency estimates very close to the generated frequencies, the method and the application are successfully validated. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie is the property of Universitatea Constantin Brancusi din Targu-Jiu and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Code: eng
        Text: English
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        PageCount: 6
        StartPage: 13
    Subjects:
      – SubjectFull: Python programming language
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Computer software
        Type: general
      – SubjectFull: Language ability testing
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      – TitleFull: ABOUT THE ACCURACY OF ESTIMATED FREQUENCIES WITH THE PyFEST SOFTWARE.
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            NameFull: Gillich, Gilbert-Rainer
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            NameFull: Nedelcu, Dorian
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            NameFull: Iancu, Vasile
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            NameFull: Gillich, Nicoleta
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          Dates:
            – D: 01
              M: 10
              Text: 2019
              Type: published
              Y: 2019
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            – TitleFull: Annals of 'Constantin Brancusi' University of Targu-Jiu. Engineering Series / Analele Universităţii Constantin Brâncuşi din Târgu-Jiu. Seria Inginerie
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