Search alternatives:
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
teer decrease » greater decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
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2021
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2022
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2023
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2024
Comparison of absolute and relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
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2025
Rate of convergence for relative errors.
Published 2025“…A significant reduction in both error types is observed, with the relative error |<i>X</i><sub><i>r</i></sub>| decreasing from approximately 10<sup>−1</sup> to 10<sup>−8</sup>. …”
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2026
Ultrafine Particulate Matter Exacerbates the Risk of Delayed Neural Differentiation: Modulation Role of METTL3-Mediated m<sup>6</sup>A Modification
Published 2025“…By employing <i>N</i>6-methyladenosine (m<sup>6</sup>A) methylated RNA immunoprecipitation sequencing and bioinformatics, we identified <i>Zic1</i> as a key target of PM<sub>0.1</sub>-induced developmental disturbances. …”
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2027
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2028
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2029
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2030
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2031
Complexity comparison of different models.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2032
Dynamic window based median filtering algorithm.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2033
Flow of operation of improved KMA.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2034
Improved DAE based on LSTM.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2035
Autoencoder structure.
Published 2025“…Therefore, the study proposes a signal automatic modulation classification model based on fixed K-mean algorithm and denoising autoencoder. The model uses fixed K-mean algorithm for feature classification and optimizes median filtering algorithm using dynamic thresholding. …”
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2036
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2037
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2038
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2039
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2040