A short introduction to quantum information and quantum by Le Bellac M.

By Le Bellac M.

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The only free parameters in this model are the cluster centers, more precisely the projections of the Gustafson Kessel cluster centers to the input space, V (x) . , 15. Workshop Computational Intelligence, 2005 - Seite 25 of parameters of the conclusion functions is computed by (17) and (18), with A1 , . . , Ac from (12) and S1 , . . , Sc from (13), just as in the Gustafson–Kessel model. We want to minimize the quadratic approximation error of the resulting Takagi–Sugeno system, JTS = 1 n n c uik fi (xk ) 2 .

Table 1 shows parts of the German and international city data sets. The German city data set contains 688 cities, and the international city data set contains 428 cities. Both lists are ordered by the number of inhabitants, so the rank k = 1 corresponds to the city with the maximum number of inhabitants. e. the differences in the yk column get lower as we proceed down the list. Fig. 1 shows the number of inhabitants versus the inverse of the rank plotted for both data sets. Instead of the rank we display the inverse of the rank, xk = 1/k, k = 1, .

773–781, 1989. , 15. : Fuzzy Clustering with a Fuzzy Covarianz Matrix. Proc. IEEE CDC, San Diego, pp. : Fuzzy Cluster Analysis, John Wiley & Sons, Chichester, 1999. : Visual Inspection of Fuzzy Clustering Results. , Roy, R. ): Advances in Soft Computing: Engineering Design and Manufacturing. Springer, London , pp. 65–76, 2003. : New approaches to noise clustering for detecting outliers. Soft computing for information mining (27th German conference on artificial intelligence - workshop proceedings), Ulm, 2004.

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