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EN
This work presents the general idea of granular description of temporal signal, particularly biomedical signal sampled with constant frequency. The main idea of presented method is based on using triangular fuzzy numbers as information granules in temporal and amplitude spaces. The amplitude space contains values of first few derivatives of underlying signal. The construction of data granules is performed using the optimization method according to some objective function, which balances the high coverage ability and the low support of fuzzy numbers. The granules (descriptors) undergo the clustering process, namely fuzzy c-means. The centroids of created clusters form a granular vocabulary and the quality of description is quantitatively assessed by reconstruction criterion. There are presented results of experiments with the electrocardiographic signal, digitally sampled and stored in MIT-BIH database. The method of numerical differentiation of function based on finite set of its values is employed, which incorporates polynomial interpolation. The paper presents results of numerical experiments which show the impact of method parameters, such as temporal window length, degree of polynomial, fuzzification parameter, on the reconstruction ability of presented method.
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