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Updated: Jan 14, 2026

Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis
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Age-dependent Dynamics of Locomotion in Caenorhabditis elegans: A Lyapunov Exponent Analysis

Published on: September 23, 2025

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神经普通微分方程用于学习和超分系统动态跨分叉

Eva van Tegelen1,2, George van Voorn1, Ioannis N Athanasiadis2

  • 1Biometris, Wageningen University and Research, Wageningen, The Netherlands.

Chaos (Woodbury, N.Y.)
|October 22, 2025
PubMed
概括

神经常规微分方程使用时间序列数据预测系统的分叉. 这种机器学习方法预测了超越训练数据的关键过渡,推进了动态系统分析.

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Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
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