An information theoretical description is given of the action of 1D maps on probability measures (e.g. on ergodic invariant measures of chaotic maps). On the basis of a detailed analysis of the elements of information flow the problem of optimum measuring of initial states for state predictions is discussed. Moreover, we give an information theoretical description of the relaxation, under the action of a map, of an initial probability distribution to any, not necessarily steady, final distribution. In this connection we formulate an H-theorem for 1D maps.
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Open AccessInformation Flow in 1D MapsJune 2, 2014
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June 2, 2014
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Open AccessDelayed Choice with Correlated PhotonsJune 2, 2014
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June 2, 2014
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June 2, 2014
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June 2, 2014
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Open AccessIntermolecular Potential Function for Ammonia-Lithium Ion Based on Ab-Initio CalculationsJune 2, 2014
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June 2, 2014
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June 2, 2014
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June 2, 2014
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June 2, 2014
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June 2, 2014
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Open AccessAnomalous X-ray Scattering Study of GeO2GlassJune 2, 2014
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June 2, 2014