The recovering of a positive density, of which a nite number of moments is assigned, is considered (in the Stieltjes and Hamburger moment problems). In the choice of the approximant the Maximum Entropy approach is adopted. Two main problems are taken into account. 1. A review of diierent criteria concerning the determinacy and indeterminacy of the innnite moment problem is presented. This revie...

Besides its importance in statistical physics and information theory, the Boltzmann-Shannon entropy S has become one of the most widely used and misused summary measures of various attributes (characteristics) in diverse fields of study. It has also been the subject of extensive and perhaps excessive generalizations. This paper introduces the concept and criteria for value validity as a means o...

Due to the complexities of objects and the vagueness of the human mind, it has attracted considerable attention from researchers studying fuzzy classification algorithms. In this paper, we propose a concept of fuzzy relative entropy to measure the divergence between two fuzzy sets. Applying fuzzy relative entropy, we prove the conclusion that patterns with high fuzziness are close to the classi...

Algorithms for classification and taxonomy based on criteria such as information entropy and its production are proposed. As an example, the feasibility of replacing a given anaesthetic by similar ones in the composition of a complex drug is studied. Some local anaesthetics currently in use are classified using characteristic chemical properties of different portions of their molecules. Many cl...

One way of using the entropy criteria in learning systems is to minimize the entropy of the error between two variables: typically, one is the output of the learning system and the other is the target. This framework has been used for regression. In this paper we show how to use the minimization of the entropy of the error for classification. The minimization of the entropy of the error implies...

We address the challenge of distinguishing physiologic interbeat interval time series from those generated by synthetic algorithms via a newly developed multiscale entropy method. Traditional measures of time series complexity only quantify the degree of regularity on a single time scale. However, many physiologic variables, such as heart rate, fluctuate in a very complex manner and present cor...

In the global competitive environment, products and services produced in software industry play a very important role making businesses more efficient. This situation causes demand for to increase rapidly. The industry's ability serve all regardless of sector has increased its product range. Especially as become open-source code, programming languages have rapidly diversified. variation reveale...

One way of using the entropy criteria in learning systems is to minimize the entropy of the error between two variables: typically, one is the output of the learning system and the other is the target. This framework has been used for regression. In this paper we show how to use the minimization of the entropy of the error for classification. The minimization of the entropy of the error implies...

in this article, we propose an adaptive image segmentation method based on saliency. First of all, we obtain the saliency map of an image via four bottom-layer feature tunnels, i.e. color, intensity, direction and energy. The energy tunnel helps to describe the outline of objects better in the saliency map. Then, we construct the target detection masks according to the greyness of pixels in the...

Customer relationship management is a multiple perspective business paradigm which helps companies gaining competitive advantage through relationships with their customers. An integrated framework for evaluating CRM performance is an important issue which is not addressed completely in previous studies. The main purpose and the most important contribution of this study is introducing a framewor...