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Showing 21 - 40 results of 2,739 for search '(((( present study algorithm ) OR ( complement box algorithm ))) OR ( neural coding algorithm ))', query time: 0.54s Refine Results
  1. 21
    Temporal response patterns determined by Dirichlet Process-based clustering algorithm across amplitudes and stimuli.

    Temporal response patterns determined by Dirichlet Process-based clustering algorithm across amplitudes and stimuli. by Dinh K. Tang (20469082)

    Published 2024
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  2. 22
    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived from the 3-level wavelet transform (WT) at four resolutions. These features were used as inputs for traditional ML algorithms. The left map demonstrates the correlation matrix of 52 features crafted from 4 resolutions of the 3-level WT, which are used as inputs for traditional ML algorithms. The heat map (on the right) is the correlation matrix after feature selection, in which features whose Pearson’s correlation coefficient is higher than 0.8 are considered highly correlated. We keep only one representative feature and remove its highly correlated features.

    Correlation matrices of handcrafted features before and after feature selection. The figure presents two heatmaps illustrating the correlation among 52 handcrafted features derived... by Quang Dung Dinh (20995766)

    Published 2025
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  3. 23
    Presentation 1_Euterpe music therapy methodology and procedure algorithms.pdf

    Presentation 1_Euterpe music therapy methodology and procedure algorithms.pdf by Tommaso Liuzzi (19956546)

    Published 2024
    “…</p>Methods<p>This paper presents a manual which specifies the procedures and algorithms of the EM, developed during a research program conducted in a pediatric hospital in Italy. …”
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  4. 24
    Code for "Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset"

    Code for "Dataset of binocularly coded steady-state visual evoked potentials recorded with an augmented reality headset" by Yufeng Ke (16539882)

    Published 2025
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  5. 25
    The folder containing the code is provided as supportive documentation associated with this paper.

    The folder containing the code is provided as supportive documentation associated with this paper. by Quxi Kuang (22493270)

    Published 2025
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  6. 26
    Algorithm for the proposed work.

    Algorithm for the proposed work. by Shuvo Biswas (21728782)

    Published 2025
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  7. 27
    Hardware_code.

    Hardware_code. by Mehdi Nadiri Andabili (22097275)

    Published 2025
    “…The presented CORDIC method eliminates multipliers by using adder and shifter operations, which provides efficient digital hardware implementation of the FHN model. …”
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  8. 28
    Software_code.

    Software_code. by Mehdi Nadiri Andabili (22097275)

    Published 2025
    “…The presented CORDIC method eliminates multipliers by using adder and shifter operations, which provides efficient digital hardware implementation of the FHN model. …”
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  9. 29
    The algorithm to define the study population.

    The algorithm to define the study population. by Michael C. Reed (6622226)

    Published 2025
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  10. 30
    Comparison of optical and silicon-based neural network implementations.

    Comparison of optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

    Published 2024
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  11. 31
    Comparison of the results achieved by the algorithm with the best <i>F</i>2 score against the results presented in [9].

    Comparison of the results achieved by the algorithm with the best <i>F</i>2 score against the results presented in [9]. by André G. Coimbra (21354135)

    Published 2025
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  12. 32
    Pseudo code.

    Pseudo code. by Xuwei Liu (6034592)

    Published 2025
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  13. 33
    The ANFIS algorithm details.

    The ANFIS algorithm details. by Mohammadmahdi Taheri (21722285)

    Published 2025
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  14. 34
    Presents the overall disproportionality analysis results, demonstrating significant signal detection across all algorithms employed.

    Presents the overall disproportionality analysis results, demonstrating significant signal detection across all algorithms employed. by Shiyu Wang (813972)

    Published 2025
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  15. 35
    Parameters of LWQPSO-SOM algorithm.

    Parameters of LWQPSO-SOM algorithm. by Yiwei Zhao (2729758)

    Published 2025
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  16. 36
    Parameters of LWQPSO-SOM algorithm.

    Parameters of LWQPSO-SOM algorithm. by Yiwei Zhao (2729758)

    Published 2025
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  17. 37
    Source Code and Dataset

    Source Code and Dataset by Swathi Ganesan (14394924)

    Published 2025
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  18. 38
    Initial parameter values for all algorithms and algorithm-specific settings.

    Initial parameter values for all algorithms and algorithm-specific settings. by Amal H. Alharbi (21755906)

    Published 2025
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  19. 39
    Comparison of power consumption in optical and silicon-based neural network implementations.

    Comparison of power consumption in optical and silicon-based neural network implementations. by Reyhane Ahmadi (14857363)

    Published 2024
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  20. 40
    Characteristics of Study Sample.

    Characteristics of Study Sample. by Vitaly Lorman (16814000)

    Published 2025
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