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Updated: May 31, 2025

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切片决定性的马尔科夫过程的高效随机模拟及其应用于神经动力学的莫里斯-莱卡尔模型

Arkady Pikovsky1

  • 1Institute for Physics and Astronomy, University of Potsdam, Karl-Liebknecht-Str. 24-25, 14476, Potsdam, Germany. arkady.pikovsky@gmail.com.

Biological cybernetics
|January 24, 2025
PubMed
概括

本研究提出了一种新的方法来模拟复杂的系统,通过将事件时间重新制定为普通微分方程. 这种方法加快了零碎决定性的马尔科夫过程的蒙特卡洛模拟,提高了计算效率.

关键词:
吉尔斯皮方法 吉尔斯皮方法混合的随机系统 混合的随机系统.河方法 河方法

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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
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