Titlebook: Maximum Entropy and Bayesian Methods; Seattle, 1991 C. Ray Smith,Gary J. Erickson,Paul O. Neudorfer Book 1992 Springer Science+Business Med

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The Evidence for Neural Networks,ly embodies ‘Occam’s razor,’ penalising over-flexible and over-complex models. The Bayesian approach helps detect poor underlying assumptions in learning models. For learning models well matched to a problem, a good correlation between generalisation ability and the Bayesian evidence is obtained.

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A Matlab Program to Calculate the Maximum Entropy Distributions,, .. In this case the .. are the geometrical moments of .. The third considers the special case where ..(.) = exp(−.), . 0,..., .. In this case the .. are the trigonometrical moments (Fourier components) of .(.). We give also some examples to illustrate the usefullness of these programs.

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The Gibbs Paradox,ibbs’ style of writing and his failure to include this explanation in his later .. This “new” understanding is not only of historical and pedagogical interest; it gives both classical and quantum statistical mechanics a different status than that presented in our textbooks, with implications for current research.

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Entropies of Likelihood Functions,s of the entropy and cross-entropy functions as groups. The relationship between the group structure and the entropy and cross-entropy functions is used to derive the result on entropies of likelihood functions.

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Entropy of Form and Hierarchic Organization,tude. The iterative construction of fractals suggests a mathematical model of the hierarchic processes of growth and differentiation whose final stationary states are defined by the MaxEnt Principle. This can be interpreted in a more general context concerning the concept of Adaptation.

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E. T. Jaynes the first edition, and expands coverage of stochastic optim.Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as a foundation for the book, which the authors have applied to business management problems developed from t