用随机变量复位法检测网络的有向交互
Detecting Directed Interactions of Networks by Random Variable Resetting
摘要：
我们提出了一种新的方法来检测一般的动态网络的有向相互作用的测量数据。通过重复目标节点的随机状态变量重置并对可测量数据进行适当平均，可以推断目标节点和响应节点之间的成对耦合函数。该方法适用于具有非线性动力学、隐变量和强噪声的广泛网络。数值结果充分验证了理论推导的正确性。
英文摘要：
We propose a novel method of detecting directed interactions of a general dynamic network from measured data. By repeating random state variable resetting of a target node and appropriately averaging over the measurable data, the pairwise coupling function between the target and the response nodes can be inferred. This method is applicable to a wide class of networks with nonlinear dynamics, hidden variables and strong noise. The numerical results have fully verified the validity of the theoretical derivation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
