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Information Geometry on Complexity and Stochastic Interaction (2001)  (Make Corrections)  (2 citations)
Nihat Ay



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Abstract: Interdependencies of stochastically interacting units are usually quanti ed by the Kullback-Leibler divergence of a stationary joint probability distribution on the set of all con gurations from the corresponding factorized distribution. This is a spatial approach which does not describe the intrinsically temporal aspects of interaction. In the present paper the setting is extended to a dynamical version where temporal interdependencies are also captured by using information geometry of... (Update)

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...it is referred to as (stochastic) interaction. In order to capture the intrinsically temporal aspects of interaction, I has been extended in [7] to the dynamical setting of Markov chains. In this case, the factorized or split Markov chains are the ones that can be composed by a...

.... to neural complexity [5,6] In order to capture intrinsically temporal aspects of dynamic interaction, I in (1) has been extended by Ay [2] to the dynamical setting of Markov chains, where it is referred to as (stochastic) interaction. The optimization of stochastic interaction...

Cited by:   More
Temporal Infomax on Markov Chains with Input Leads to Finite.. - Wennekers, Ay   (Correct)
Dynamical properties of strongly interacting Markov chains - Ay, Wennekers (2001)   (Correct)

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BibTeX entry:   (Update)

Ay, N. (2001c) Information Geometry on Complexity and Stochastic Interaction. Submitted. 28 http://citeseer.ist.psu.edu/ay01information.html   More

@misc{ ay-information,
  author = "N. Ay",
  title = "Information Geometry on Complexity and Stochastic Interaction",
  text = "Ay, N. (2001c) Information Geometry on Complexity and Stochastic Interaction.
    Submitted. 28",
  url = "citeseer.ist.psu.edu/ay01information.html" }
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