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Showing 1 - 20 results of 1,603 for search '(((( implement based algorithm ) OR ( elements lasso algorithm ))) OR ( level coding algorithm ))*', query time: 0.43s Refine Results
  1. 1
    IAM and IEM muxes control code.

    IAM and IEM muxes control code. by Ayesha Waris (21368446)

    Published 2025
    “…The presented architectures are implemented on Xilinx Artix-7 XC7A100T-3 device using Vivado Design Suite 2022.2 and coded using Verilog HDL. …”
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  2. 2
    Parameter configuration for ChildEmoNet algorithm implementation.

    Parameter configuration for ChildEmoNet algorithm implementation. by Zhang Shanshan (22272359)

    Published 2025
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  3. 3
    Illustration of the recursive objective space exploration process implemented by the ROSE algorithm.

    Illustration of the recursive objective space exploration process implemented by the ROSE algorithm. by Ihab Hashem (21156806)

    Published 2025
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  4. 4
    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets.

    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. by Tomokaze Shiratori (9635271)

    Published 2024
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  5. 5
    Flow chart of implementation of metaheuristic algorithm-PI control BLDC motor.

    Flow chart of implementation of metaheuristic algorithm-PI control BLDC motor. by Fizza Shafique (19996292)

    Published 2024
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  6. 6
    Main code.

    Main code. by Jingguo Bi (21439766)

    Published 2025
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  7. 7
    The details of the results related to the evaluated algorithms.

    The details of the results related to the evaluated algorithms. by Mohammadreza Namdar (22439057)

    Published 2025
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  8. 8
    Resource utilization of modules in proposed implementations.

    Resource utilization of modules in proposed implementations. by Ayesha Waris (21368446)

    Published 2025
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  9. 9
    The results of bug reports classification by the MNB algorithm.

    The results of bug reports classification by the MNB algorithm. by Mohammadreza Namdar (22439057)

    Published 2025
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  10. 10
    The results of bug reports classification by the LR algorithm.

    The results of bug reports classification by the LR algorithm. by Mohammadreza Namdar (22439057)

    Published 2025
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  11. 11
    The results of bug reports classification by the RF algorithm.

    The results of bug reports classification by the RF algorithm. by Mohammadreza Namdar (22439057)

    Published 2025
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  12. 12
    The results of bug reports classification by the GNB algorithm.

    The results of bug reports classification by the GNB algorithm. by Mohammadreza Namdar (22439057)

    Published 2025
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  13. 13
    The results of bug reports classification by the SVM algorithm.

    The results of bug reports classification by the SVM algorithm. by Mohammadreza Namdar (22439057)

    Published 2025
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  14. 14
    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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  15. 15
    Computation time as a function of the sample size on the chain graph dataset.

    Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  16. 16
    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  17. 17
    Computation time as a function of the sample size on the random graph dataset.

    Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  18. 18
    F1 score of edges selected through cross-validation on the chain graph dataset.

    F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  19. 19
    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  20. 20
    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10).

    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10). by Tomokaze Shiratori (9635271)

    Published 2024
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