Search alternatives:
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
greatest decrease » treatment decreased (Expand Search), greater increase (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), teer decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), gy decreased (Expand Search)
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2121
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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2122
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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2123
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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2124
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2125
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2126
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2127
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2128
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2129
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2130
Frontier Analysis Based on ASDR and SDI.
Published 2025“…The frontier analysis identified 15 countries with the greatest potential for improvement. According to the BAPC model, the ASDR for females is projected to rise across the 20–80 age group, while for males, the increase is particularly pronounced in the 55–75 age group. …”
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2131
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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2132
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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2133
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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2134
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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2135
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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2136
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2137
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2138
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2139
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2140