Read e-book online Artificial Intelligence and Soft Computing: 12th PDF

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By Yoichi Hayashi (auth.), Leszek Rutkowski, Marcin Korytkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)

ISBN-10: 3642386571

ISBN-13: 9783642386572

ISBN-10: 364238658X

ISBN-13: 9783642386589

The two-volume set LNAI 7894 and LNCS 7895 constitutes the refereed complaints of the twelfth foreign convention on synthetic Intelligence and smooth Computing, ICAISC 2013, held in Zakopane, Poland in June 2013. The 112 revised complete papers awarded including one invited paper have been conscientiously reviewed and chosen from 274 submissions. The fifty seven papers incorporated within the first quantity are equipped within the following topical sections: neural networks and their functions; fuzzy platforms and their purposes; trend type; and computing device imaginative and prescient, picture and speech analysis.

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Read or Download Artificial Intelligence and Soft Computing: 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Proceedings, Part I PDF

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Additional info for Artificial Intelligence and Soft Computing: 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Proceedings, Part I

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5 46 52 1 Fig. 6. f. [36]). Right) The design obtained by our optimization algorithm started from the Hilbert space-filling curve based configuration. Both designs are plotted together with isolines of the squared power function. 6 Conclusions We have presented a scheme of using constrained non-linear programming to calculate the optimal configurations of centers for a radial basis interpolation process. From eight designs obtained by the proposed optimization algorithm seven configurations give objective function values lower than that generated as an initial configuration by DMSW algorithm [6].

The new configuration decreases the Runge phenomenon compared to the configuration obtained by DMSW algorithm [6]. 5 1 Fig. 1. 5 1 Fig. 2. 2 27 Two Dimensional Example In this section we present the performance of the proposed design optimization algorithm launched from 5 randomly generated points forming a Latin hypercube [33], one optimization started from a Sierpi´ nski filling curve configuration of centers [36], another one started from a Hilbert filling curve configuration of centers [36] and one optimization started from the quasi-optimal configuration of centers generated by DMSW algorithm [6].

Sampling multidimensional signals by a new class of quasi-random sequences. Multidimensional System and Signal Processing 23, 237–253 (2012) 40. : Scattered Data Approximation. Cambridge University Press (2005) 41. : Local error estimates for radial basis function interpolation of scattered data. IMA J. Numer. Anal. pl Abstract. This paper presents the parallel architecture of the Jordan network learning algorithm. The proposed solution is based on the high parallel three dimensional structures to speed up learning performance.

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Artificial Intelligence and Soft Computing: 12th International Conference, ICAISC 2013, Zakopane, Poland, June 9-13, 2013, Proceedings, Part I by Yoichi Hayashi (auth.), Leszek Rutkowski, Marcin Korytkowski, Rafał Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)


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