We study the entropy function of two N = 2 string compactifications obtained as freely acting orbifolds of N = 4 theories : the STU model and the FHSV model. The Gauss-Bonnet term for these compactifications is known precisely. We apply the entropy function formalism including the contribution of this four derivative term and evaluate the entropy of dyons to the first subleading order in charge...

This paper presents a new multi-objective mathematical model for the redundancy allocation problem with the choices of a redundancy strategy and component type in series-parallel systems. The model considers entropy measure which is a measure of uncertainty in the information theory. For the first time, the model maximizes the reliability and entropy of the system and minimizes the nonlinear co...

This paper presents a new Chinese chunking method based on maximum entropy Markov models. We firstly present two types of Chinese chunking specifications and data sets, based on which the chunking models are applied. Then we describe the hidden Markov chunking model and maximum entropy chunking model. Based on our analysis of the two models, we propose a maximum entropy Markov chunking model th...

The technology of support vector machines (SVM) is being widely used in many research fields at present, but standard SVM does not provide posterior probability that is needed in many uncertain classification problems. To solve this problem, a probability SVM model is built firstly, then the cross entropy and relative cross entropy model for classification problems are built. Finally, the metho...

The entropy theory has been widely applied in hydrology for probability inference based on incomplete information and the principle of maximum entropy. Meanwhile, copulas have been extensively used for multivariate analysis and modeling the dependence structure between hydrologic and climatic variables. The underlying assumption of the principle of maximum entropy is that the entropy variables ...

In this paper, we introduce a new entropy-like invariant, named Hausdorff metric entropy, for finitely generated semigroups acting on compact metric spaces from a set-valued view and study its properties. We establish the relation between Hausdorff metric entropy and topological entropy of a semigroup defined by Bis. Some examples with positive or zero Hausdorff metric entropy are given. Moreov...

In this paper, we show that in order to obtain the Tsallis entropy rate for stochastic processes, we can use the limit of conditional entropy, as it was done for the case of Shannon and Renyi entropy rates. Using that we can obtain Tsallis entropy rate for stationary Gaussian processes. Finally, we derive the relation between Renyi, Shannon and Tsallis entropy rates for stationary Gaussian proc...

In statistical physics, useful notions of entropy are defined with respect to some coarse graining procedure over a microscopic model. Here we consider some special problems that arise when the microscopic model is taken to be relativistic quantum field theory. These problems are associated with the existence of an infinite number of degrees of freedom per unit volume. Because of these the micr...

Maximum entropy models have become popular statistical models in neuroscience and other areas in biology and can be useful tools for obtaining estimates of mutual information in biological systems. However, maximum entropy models fit to small data sets can be subject to sampling bias; i.e., the true entropy of the data can be severely underestimated. Here, we study the sampling properties of es...

In traditional n-gram language modeling, we collect the statistics for all n-grams observed in the training set up to a certain order. The model can then be pruned down to a more compact size with some loss in modeling accuracy. One of the more principled methods for pruning the model is the entropy-based pruning proposed by Stolcke (1998). In this paper, we present an algorithm for incremental...