Cargando…
Towards a Framework for Observational Causality from Time Series: When Shannon Meets Turing
We propose a tensor based approach to infer causal structures from time series. An information theoretical analysis of transfer entropy (TE) shows that TE results from transmission of information over a set of communication channels. Tensors are the mathematical equivalents of these multichannel cau...
Autor principal: | Sigtermans, David |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7516903/ https://www.ncbi.nlm.nih.gov/pubmed/33286199 http://dx.doi.org/10.3390/e22040426 |
Ejemplares similares
-
Determining Causal Skeletons with Information Theory
por: Sigtermans, David
Publicado: (2020) -
Causal Shannon–Fisher Characterization of Motor/Imagery Movements in EEG
por: Baravalle, Román, et al.
Publicado: (2018) -
Fisher–Shannon Complexity Analysis of High-Frequency Urban Wind Speed Time Series
por: Guignard, Fabian, et al.
Publicado: (2019) -
David Shannon
Publicado: (1933) -
On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid
por: Nielsen, Frank
Publicado: (2020)