https://elib.bsu.by:443/handle/123456789/51078 Tue, 21 Apr 2026 06:30:03 GMT 2026-04-21T06:30:03Z https://elib.bsu.by:443/retrieve/165143/111111сж.jpg https://elib.bsu.by:443/handle/123456789/51078 https://elib.bsu.by:443/handle/123456789/51366 Заглавие документа: On the Computational Accuracy of the Heuristic Method of Possibilistic Clustering Авторы: Damaratski, A.; Novikau, D. Аннотация: The problem of computational efforts of a heuristic method of possibilistic clustering based on the concept of allotment among fuzzy clusters is considered in the paper. The basic concepts of the method of clustering based on the allotment concept are considered. The dependence of the classification results upon the accuracy of the computation is illustrated on the example of Anderson’s Iris data. Preliminary conclusions are formulated. Thu, 01 Jan 2009 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/51366 2009-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/51364 Заглавие документа: Image Restoration Spectral Techniques Авторы: Milukova, O.; Kober, V.; Ovseevich, I. A. Аннотация: Since the single-channel framework of image restoration possesses serious conceptual and numerical problems, in this paper we present a general concept of image signal recovering. We also propose a space-variant restoration method using sliding spectral transforms. To provide image processing in real time, fast recursive algorithm for computing the sliding sinusoidal transform is utilized. Computer simulation results using a real image are provided and discussed. Thu, 01 Jan 2009 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/51364 2009-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/51362 Заглавие документа: Texture Indexes and Gray Level Size Zone Matrix Application to Cell Nuclei Classification Авторы: Thibault, G.; Fertil, B.; Navarro, C.; Pereira, S.; Cau, P.; Levy, N.; Sequeira, J.; Mari, J. J. Аннотация: In this paper, we present a study on the characterization and the classification of textures. This study is performed using a set of values obtained by the computation of indexes. To obtain these indexes, we extract a set of data with two techniques: the computation of matrices which are statistical representations of the texture and the computation of "measures". These matrices and measures are subsequently used as parameters of a function bringing real or discrete values which give information about texture features. A model of texture characterization is built based on this numerical information, for example to classify textures. An application is proposed to classify cells nuclei in order to diagnose patients affected by the Progeria disease. Thu, 01 Jan 2009 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/51362 2009-01-01T00:00:00Z https://elib.bsu.by:443/handle/123456789/51358 Заглавие документа: Recognizing Linguistic Models as a Component of Base Linguistic Resources of Natural Language Авторы: Rubashko, N. Аннотация: This paper presents the problems of the development of recognizing linguistic models for natural language text analysis. These models are the important component of any linguistic knowledge base. Using the suggested approach we can develop recognizing linguistic models for any natural language. Examples of the recognizing linguistic models used for the analysis of inflectional languages (Belarusian and Russian) are given in the paper. Thu, 01 Jan 2009 00:00:00 GMT https://elib.bsu.by:443/handle/123456789/51358 2009-01-01T00:00:00Z