Shipley et al. (Reports, 3 November 2006, p. 812) predicted plant community composition and relative abundances with a high level of accuracy by maximizing Shannon’s index of information entropy (species diversity), subject to constraints on plant trait averages. We show that the entropy maximization assumption is relatively unimportant and that the high accuracy is due largely to a statistical...

We introduced the concept of C-space entropy recently in [9] as a measure of knowledge of Cspace for sensor-based exploration and path planning for general robot-sensor systems. The robot plans the next sensing action to maximally reduce the expected C-space entropy, also called the Maximal expected Entropy Reduction, or MER criterion. The resulting view planning algorithms showed significant i...

The asymptotic convergence of probability density function (pdf) and convergence of differential entropy are examined for the non-stationary processes that follow the maximum entropy principle (MaxEnt) and maximum entropy production principle (MEPP). Asymptotic convergence of pdf provides new justification of MEPP while convergence of differential entropy is important in asymptotic analysis of ...

Abstract In this paper, we consider the methods of obtaining maximum entropy multivariate distributions via Burg’s measure of entropy under the constraints that the marginal distributions or the marginals and covariance matrix are prescribed. Next, a numerical method is considered for the cases of unavailable closed form of solutions. Finally, the method is illustrated via a numerical example.

This paper describes a method for calculating short-range magnetic order in itinerant magnets. An energy and an entropy are assigned to configurations of the magnetization. The energy comes from the electronic structure and the entropy from the number of configurations satisfying constraints on the short-range order.

We find the value of constants related to constraints in characterization of some known statistical distributions and then we proceed to use the idea behind maximum entropy principle to derive generalized version of this distributions using the Tsallis’ and Renyi information measures instead of the well-known Bolztmann-Gibbs-Shannon. These generalized distributions will depend on q ∈ R and in t...

Motivated by the success of iterative decoding algorithms, we consider the general problem of making inferences based on observed data, which are known a-priori to satisfy multiple sets of constraints. We consider relative entropy minimisation and an iterative algorithm for its calculation, which exploits the presence of multiple constraints. Using these principles, optimal iterative decoders, ...

This paper proposes the use of maximum entropy techniques for text classification. Maximum entropy is a probability distribution estimation technique widely used for a variety of natural language tasks, such as language modeling, part-of-speech tagging, and text segmentation. The underlying principle of maximum entropy is that without external knowledge, one should prefer distributions that are...

We introduce a concept of independence entropy for symbolic dynamical systems. This notion of entropy measures the extent to which one can freely insert symbols in positions without violating the constraint defined by the shift space. We show that for a certain class of one-dimensional shift spaces X, the independence entropy coincides with the limiting, as d tends to infinity, topological entr...

The extension of the phases of the structure factors of the organic crystal C(25)H(25)NO(2) from 77 starting individual phases using the maximum-entropy method is reported. These starting phases were determined from 90 experimental triplet phases calculated from 215 measured psi-scan three-beam and four-beam diffraction profiles obtained with a rotating-anode X-ray source, where the psi scans w...