يعرض 1 - 20 نتائج من 6,691 نتيجة بحث عن '(( algorithm phase function ) OR ((( algorithm within function ) OR ( algorithm b function ))))', وقت الاستعلام: 0.52s تنقيح النتائج
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    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer حسب Morgan Najera (21540776)

    منشور في 2025
    "…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …"
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    Flowchart of the phase optimization algorithm. حسب Maxim Terekhov (3429614)

    منشور في 2021
    "…<p>At stage II, phase vectors {Φ<sup>top</sup>} providing cost function values F<sub>c</sub> above 90% of maximum are selected as initial condition {Φ<sub>0</sub>} for iterative NLS-search and selection of the optimum vectors {Φ<sup>opt</sup>}. …"
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    TV-BayesOpt algorithm performance for tracking a gradual drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. حسب John E. Fleming (8533956)

    منشور في 2023
    "…Panel B illustrates the associated average regret for the TV-BayesOpt algorithm at tracking the true optimum phase value in comparison to when static BayesOpt was implemented alone. …"
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    TV-BayesOpt algorithm performance for tracking a periodic drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. حسب John E. Fleming (8533956)

    منشور في 2023
    "…Panel B illustrates the associated average regret for the TV-BayesOpt algorithm at tracking the true optimum phase value in comparison to when static BayesOpt was implemented alone. …"
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    TV-BayesOpt algorithm performance for tracking a superimposed (gradual and periodic) drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*. حسب John E. Fleming (8533956)

    منشور في 2023
    "…Panel B illustrates the associated average regret for the TV-BayesOpt algorithm at tracking the true optimum phase value in comparison to when static BayesOpt was implemented alone. …"
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    The SSIM for the different algorithms. حسب Bingbing Li (461702)

    منشور في 2024
    "…Different types of noise require different denoising algorithms and techniques to maintain image quality and fidelity. …"
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    Linear-regression-based algorithms succeed at identifying the correct functional groups in synthetic data, and multi-group algorithms recover more information. حسب Yuanchen Zhao (12905580)

    منشور في 2024
    "…<p>(A), (B) Algorithm performance, evaluated over 50 simulated datasets generated as described in <a href="http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1012590#pcbi.1012590.g001" target="_blank">Fig 1</a> with <i>N</i> = 3 true groups, 900 samples and 10% simulated measurement noise. …"