Relative Entropy and Identification of Gibbs Measures in Dynamical Systems

In this work we explore the idea of using the relative entropy of ergodic measures for the identification of Gibbs measures in dynamical systems. The question we face is how to estimate the thermodynamic potential (together with a grammar) from a sample produced by the corresponding Gibbs state.

[1]  R. A. Leibler,et al.  On Information and Sufficiency , 1951 .

[2]  Solomon Kullback,et al.  Information Theory and Statistics , 1960 .

[3]  C. Caramanis What is ergodic theory , 1963 .

[4]  Meir Smorodinsky,et al.  Ergodic Theory Entropy , 1971 .

[5]  R. Bowen Equilibrium States and the Ergodic Theory of Anosov Diffeomorphisms , 1975 .

[6]  P. Billingsley,et al.  Probability and Measure , 1980 .

[7]  R. Katz On Some Criteria for Estimating the Order of a Markov Chain , 1981 .

[8]  Basilis Gidas,et al.  Parameter Estimation for Gibbs Distributions from Partially Observed Data , 1992 .

[9]  Benjamin Weiss,et al.  How Sampling Reveals a Process , 1990 .

[10]  W. Parry,et al.  Zeta functions and the periodic orbit structure of hyperbolic dynamics , 1990 .

[11]  A. Raftery,et al.  Estimation and Modelling Repeated Patterns in High Order Markov Chains with the Mixture Transition Distribution Model , 1994 .

[12]  P. Collet,et al.  Maximum Likelihood and Minimum Entropy Identification of Grammars , 1995, ArXiv.

[13]  Self-similarity and finite-time intermittent effects in turbulent sequences , 1996 .

[14]  On a discrete dynamical model for local turbulence , 1996 .

[15]  L. Barreira,et al.  On a general concept of multifractality: Multifractal spectra for dimensions, entropies, and Lyapunov exponents. Multifractal rigidity. , 1997, Chaos.

[16]  John T. Lewis,et al.  Reconstruction sequences and equipartition measures: An examination of the asymptotic equipartition property , 1997, IEEE Trans. Inf. Theory.