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Updated: Jul 22, 2025

Closed-loop Neuro-robotic Experiments to Test Computational Properties of Neuronal Networks
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Published on: March 2, 2015

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带有不规则和杂数据的神经普通微分方程

Pawan Goyal1, Peter Benner1

  • 1Max Planck Institute for Dynamics of Complex Technical Systems, Standtorstrasse 1, 39106 Magdeburg, Germany.

Royal Society open science
|July 21, 2023
PubMed
概括

这项研究引入了一种使用深度神经网络和神经普通微分方程 (ODEs) 来基于噪音数据建模物理过程的新方法. 该方法有效地重建微分方程,即使采用不规则的抽样和噪声.

关键词:
动态系统是动态系统.机器学习是机器学习.神经网络的神经网络的神经网络神经常规微分方程 神经常规微分方程噪音数据 噪音数据

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