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    Wyświetlanie 1-4 z 4
    Tytuł:
    Accurate identification on individual similar communication emitters by using HVG-NTE feature
    Autorzy:
    Li, Ke
    Ge, Wei
    Yang, Xiaoya
    Xu, Zhengrong
    Powiązania:
    https://bibliotekanauki.pl/articles/2128146.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    communication emitter
    identification
    feature extraction
    HVG
    NTE
    emiter komunikacji
    identyfikacja
    wyodrębnianie cech
    Opis:
    Individual identification of similar communication emitters in the complex electromagnetic environment has great research value and significance in both military and civilian fields. In this paper, a feature extraction method called HVG-NTE is proposed based on the idea of system nonlinearity. The shape of the degree distribution, based on the extraction of HVG degree distribution, is quantified with NTE to improve the anti-noise performance. Then XGBoost is used to build a classifier for communication emitter identification. Our method achieves better recognition performance than the state-of-the-art technology of the transient signal data set of radio stations with the same plant, batch, and model, and is suitable for a small sample size.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136741, 1--6
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Accurate identification on individual similar communication emitters by using HVG-NTE feature
    Autorzy:
    Li, Ke
    Ge, Wei
    Yang, Xiaoya
    Xu, Zhengrong
    Powiązania:
    https://bibliotekanauki.pl/articles/2173613.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    communication emitter
    identification
    feature extraction
    HVG
    NTE
    emiter komunikacji
    identyfikacja
    wyodrębnianie cech
    Opis:
    Individual identification of similar communication emitters in the complex electromagnetic environment has great research value and significance in both military and civilian fields. In this paper, a feature extraction method called HVG-NTE is proposed based on the idea of system nonlinearity. The shape of the degree distribution, based on the extraction of HVG degree distribution, is quantified with NTE to improve the anti-noise performance. Then XGBoost is used to build a classifier for communication emitter identification. Our method achieves better recognition performance than the state-of-the-art technology of the transient signal data set of radio stations with the same plant, batch, and model, and is suitable for a small sample size.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; art. no. e136741
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Research on communication emitter identification based on semi-supervised dimensionality reduction in complex electromagnetic environment
    Autorzy:
    Ge, Wei
    Qi, Lin
    Tong, Lin
    Zhu, Jun
    Zhang, Jing
    Zhao, Dongyang
    Li, Ke
    Powiązania:
    https://bibliotekanauki.pl/articles/27311449.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    communication emitter identification
    feature extraction
    dimensionality reduction
    VMD
    ESDA
    variational mode decomposition
    exponential semi-supervised discriminant analysis
    identyfikacja emitera komunikacyjnego
    ekstrakcja cech
    redukcja wymiarowości
    rozkład w trybie wariacyjnym
    analiza dyskryminacyjna wykładnicza półnadzorowana
    Opis:
    The individual identification of communication emitters is a process of identifying different emitters based on the radio frequency fingerprint features extracted from the received signals. Due to the inherent non-linearity of the emitter power amplifier, the fingerprints provide distinguishing features for emitter identification. In this study, approximate entropy is introduced into variational mode decomposition, whose features performed in each mode which is decomposed from the reconstructed signal are extracted while the local minimum removal method is used to filter out the noise mode to improve SNR. We proposed a semi-supervised dimensionality reduction method named exponential semi-supervised discriminant analysis in order to reduce the high-dimensional feature vectors of the signals, and LightGBM is applied to build a classifier for communication emitter identification. The experimental results show that the method performs better than the state-of-the-art individual communication emitter identification technology for the steady signal data set of radio stations with the same plant, batch and model.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 4; art. no. e145766
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    A BIM technology-based underwater structure damage identification and management method
    Autorzy:
    Li, Xiaofei
    Su, Rongrong
    Cheng, Peng
    Sun, Heming
    Meng, Qinghang
    Song, Taiyi
    Wei, Mengpu
    Zhang, Chen
    Powiązania:
    https://bibliotekanauki.pl/articles/2204531.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    building information modeling
    underwater structural disease
    damage identification
    deep learning
    modelowanie informacji o budynku
    identyfikacja uszkodzeń
    uczenie głębokie
    uszkodzenie podwodnej konstrukcji
    Opis:
    With the continuous development of bridge technology, the condition assessment of large bridges has gradually attracted attention. Structural Health Monitoring (SHM) technology provides valuable information about a structure's existing health, keeping it safe and uninterrupted use under various operating conditions by mitigating risks and hazards on time. At the same time, the problem of bridge underwater structure disease is becoming more obvious, affecting the safe operation of the bridge structure. It is necessary to test the bridge’s underwater structure. This paper develops a bridge underwater structure health monitoring system by combining building information modeling (BIM) and an underwater structure damage algorithm. This paper is verified by multiple image recognition networks, and compared with the advantages of different networks, the YOLOV4 network is used as the main body to improve, and a lightweight convolutional neural network (Lite-yolov4) is built. At the same time, the accuracy of disease identification and the performance of each network are tested in various experimental environments, and the reliability of the underwater structure detection link is verified.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 2; art. no. e144602
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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