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Generalized Measures of Information Transfer

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arxiv 1102.1507 v1 pith:VDEYPONP submitted 2011-02-08 physics.data-an cs.ITmath.DSmath.IT

classification physics.data-ancs.ITmath.DSmath.IT
keywords transferdistinguishentropyextendinformationmeasuresanalyzingcomplementary
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Transfer entropy provides a general tool for analyzing the magnitudes and directions---but not the \emph{kinds}---of information transfer in a system. We extend transfer entropy in two complementary ways. First, we distinguish state-dependent from state-independent transfer, based on whether a source's influence depends on the state of the target. Second, for multiple sources, we distinguish between unique, redundant, and synergistic transfer. The new measures are demonstrated on several systems that extend examples from previous literature.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Beyond integrated information: A taxonomy of information dynamics phenomena

    q-bio.NC 2019-09 conditional novelty 8.0 of 10

    ΦID decomposes the mutual information between the past and future states of a bivariate Markov process into sixteen atoms, showing that integrated information measures blend distinct dynamical modes such as storage, t...

  2. A Novel Approach to the Partial Information Decomposition

    cs.IT 2019-08 accept novelty 7.0 of 10

    A Blackwell-order-based definition of redundancy yields a new multivariate PID measure that satisfies natural axioms and is operationally grounded, while its union dual reduces to an existing measure.

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