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连续状态输入-输出系统的特定转移熵及其他状态依赖转移熵

Specific transfer entropy and other state-dependent transfer entropies for continuous-state input-output systems.

作者信息

Darmon David, Rapp Paul E

机构信息

Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814, USA and The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, Maryland 20817, USA.

Department of Military and Emergency Medicine, Uniformed Services University of the Health Sciences, Bethesda, Maryland 20814, USA.

出版信息

Phys Rev E. 2017 Aug;96(2-1):022121. doi: 10.1103/PhysRevE.96.022121. Epub 2017 Aug 9.

Abstract

Since its original formulation in 2000, transfer entropy has become an invaluable tool in the toolbox of nonlinear dynamicists working with empirical data. Transfer entropy and its generalizations provide a precise definition of uncertainty and information transfer that are central to the coupled systems studied in nonlinear science. However, a canonical definition of state-dependent transfer entropy has yet to be introduced. We introduce a candidate measure, the specific transfer entropy, and compare its properties to both total and local transfer entropy. Specific transfer entropy makes possible both state- and time-resolved analysis of the predictive impact of a candidate input system on a candidate output system. We also present principled methods for estimating total, local, and specific transfer entropies from empirical data. We demonstrate the utility of specific transfer entropy and our proposed estimation procedures with two model systems, and find that specific transfer entropy provides more, and more easily interpretable, information about an input-output system compared to currently existing methods.

摘要

自2000年最初提出以来,转移熵已成为处理经验数据的非线性动力学家工具包中一项非常有价值的工具。转移熵及其推广形式提供了不确定性和信息传递的精确定义,而这些对于非线性科学中研究的耦合系统至关重要。然而,尚未引入状态依赖转移熵的规范定义。我们引入了一种候选度量,即特定转移熵,并将其性质与总转移熵和局部转移熵进行比较。特定转移熵使得对候选输入系统对候选输出系统的预测影响进行状态和时间分辨分析成为可能。我们还提出了从经验数据估计总转移熵、局部转移熵和特定转移熵的原理性方法。我们用两个模型系统展示了特定转移熵和我们提出的估计程序的效用,并且发现与现有方法相比,特定转移熵能提供更多且更易于解释的关于输入 - 输出系统的信息。

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