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Updated: Jun 23, 2025

Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons
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Author Spotlight: Alignment of Synchronized Time-Series Data Using the Characterizing Loss of Cell Cycle Synchrony Model for Cross-Experiment Comparisons

Published on: June 9, 2023

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为具有固定和自适应合强度的复杂延迟网络设计一个强大的基于同步的拓观察器

Yanqin Sun1,2,3, Huaiyu Wu1,3, Zhihuan Chen1,3

  • 1School of Information Science and Engineering, Wuhan University of Science and Technology, Wuhan 430081, China.

Entropy (Basel, Switzerland)
|June 26, 2024
PubMed
概括

这项研究引入了一个强大的拓观察器 (STO) 来识别复杂的网络结构,即使有隐藏或不确定的信息. 对于各种网络类型和合强度,STO方法有效地工作,性能优于现有的方法.

关键词:
复杂的延迟网络复杂的延迟网络.固定和自适应合器的强度强度.基于稳健同步的观察者.拓识别 拓识别

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