Fourier-domain transfer entropy spectrum
Abstract
We propose the Fourier-domain transfer entropy spectrum, a novel generalization of transfer entropy, as a model-free metric of causality. For arbitrary systems, this approach systematically quantifies the causality among their different system components rather than merely analyze systems as entireties. The generated spectrum offers a rich-information representation of time-varying latent causal relations, efficiently dealing with non-stationary processes and high-dimensional conditions. We demonstrate its validity in the aspects of parameter dependence, statistic significance test, and sensibility. An open-source multi-platform implementation of this metric is developed and computationally applied on neuroscience data sets and diffusively coupled logistic oscillators.
Cite
@article{arxiv.2110.06480,
title = {Fourier-domain transfer entropy spectrum},
author = {Yang Tian and Yaoyuan Wang and Ziyang Zhang and Pei Sun},
journal= {arXiv preprint arXiv:2110.06480},
year = {2021}
}