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Titlebook: Artificial Intelligence and Soft Computing; 12th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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樓主: Objective
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發(fā)表于 2025-3-26 22:21:05 | 只看該作者
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發(fā)表于 2025-3-27 03:23:49 | 只看該作者
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發(fā)表于 2025-3-27 05:32:38 | 只看該作者
https://doi.org/10.1007/978-3-642-66599-8implementations were measured and compared. In the ESN case, speed-ups were observed at reservoir sizes greater than 1,024. The first significant speed-ups of 6 and and 5 were observed at a reservoir size of 2,048 in double and single precision respectively. In the case of Tikhonov Regularisation, no significant speed-ups were observed.
34#
發(fā)表于 2025-3-27 09:30:43 | 只看該作者
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發(fā)表于 2025-3-27 14:19:41 | 只看該作者
https://doi.org/10.1007/978-3-662-21539-5 terms. The proposed approach is based on a random sieve that aims at selecting only necessary RBF’s by a hierarchy of a large number of random mixing of candidate RBF’s and testing their significance. The results of simulations are also reported.
36#
發(fā)表于 2025-3-27 18:02:32 | 只看該作者
A New Method of Centers Location in Gaussian RBF Interpolation Networkse Latin hypercube designs and a space-filling curve based space-filling designs as starting points for the optimization procedure. We restrict our attention to 1-D and 2-D interpolation problems. Finally, we provide results of several numerical experiments. We compare the performance of this new method with the method of [6].
37#
發(fā)表于 2025-3-27 22:41:20 | 只看該作者
38#
發(fā)表于 2025-3-28 05:18:03 | 只看該作者
Testing the Generalization of Feedforward Neural Networks with Median Neuron Input Function The MIF networks were designed to be fault tolerant but we expect them to have also improved generalization ability. Results of first experimental simulations are presented and described in this article. Potentially improved performance of the MIF networks is demonstrated.
39#
發(fā)表于 2025-3-28 06:17:08 | 只看該作者
40#
發(fā)表于 2025-3-28 13:06:19 | 只看該作者
Conference proceedings 2013ft Computing, ICAISC 2013, held in Zakopane, Poland in June 2013. The 112 revised full papers presented together with one invited paper were carefully reviewed and selected from 274 submissions. The 57 papers included in the first volume are organized in the following topical sections: neural networ
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