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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2022
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2212.05728 |
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| _version_ | 1866914784706822144 |
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| author | Østergaard, Jan Boubakani, Payam |
| author_facet | Østergaard, Jan Boubakani, Payam |
| contents | We present a new decomposition of transfer entropy to characterize the degree of synergy- and redundancy-dominated influence a time series has upon the interaction between other time series. We prove the existence of a class of time series, where the early past of the conditioning time series yields a synergistic effect upon the interaction, whereas the late past has a redundancy-dominated effect. In general, different parts of the past can have different effects. Our information theoretic quantities are easy to compute in practice, and we demonstrate their usage on real-world brain data. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2212_05728 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Synergy and Redundancy Dominated Effects in Time Series via Transfer Entropy Decompositions Østergaard, Jan Boubakani, Payam Information Theory We present a new decomposition of transfer entropy to characterize the degree of synergy- and redundancy-dominated influence a time series has upon the interaction between other time series. We prove the existence of a class of time series, where the early past of the conditioning time series yields a synergistic effect upon the interaction, whereas the late past has a redundancy-dominated effect. In general, different parts of the past can have different effects. Our information theoretic quantities are easy to compute in practice, and we demonstrate their usage on real-world brain data. |
| title | Synergy and Redundancy Dominated Effects in Time Series via Transfer Entropy Decompositions |
| topic | Information Theory |
| url | https://arxiv.org/abs/2212.05728 |