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Titlebook: Artificial Neural Networks - ICANN 2001; International Confer Georg Dorffner,Horst Bischof,Kurt Hornik Conference proceedings 2001 Springer

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樓主: risky-drinking
51#
發(fā)表于 2025-3-30 08:23:57 | 只看該作者
Neural Networks for Adaptive Processing of Structured Datahe ability to recognize and classify these patterns is fundamental for several applications that use, generate or manipulate structures. In this paper I review some of the concepts underpinning Recursive Neural Networks, i.e. neural network models able to deal with data represented as directed acyclic graphs.
52#
發(fā)表于 2025-3-30 12:57:11 | 只看該作者
53#
發(fā)表于 2025-3-30 19:32:53 | 只看該作者
Architecture Selection in NLDA Networksork we study the architecture selection problem for NLDA networks. We shall derive asymptotic distribution results for NLDA weights, from which Wald like tests can be derived. We also discuss how to use them to make decisions on unit relevance based on the acceptance or rejection of a certain null hypothesis.
54#
發(fā)表于 2025-3-30 22:15:17 | 只看該作者
Approximation of Bayesian Discriminant Function by Neural Networks in Terms of Kullback-Leibler Infoork, having rather a small number of hidden layer units, can approximate the Bayesian discriminant function for the two category classification if the log ratio of the a posteriori probability is a polynomial. The accuracy of approximation is measured by the Kullback-Leibler information. An extension to the multi-category case is also discussed.
55#
發(fā)表于 2025-3-31 04:26:09 | 只看該作者
https://doi.org/10.1007/3-540-44668-0Artificial neural networks; Beowulf; Controller Area Network (CAN); Online; Segment; artificial intellige
56#
發(fā)表于 2025-3-31 07:38:28 | 只看該作者
978-3-540-42486-4Springer-Verlag Berlin Heidelberg 2001
57#
發(fā)表于 2025-3-31 11:24:35 | 只看該作者
58#
發(fā)表于 2025-3-31 13:27:39 | 只看該作者
59#
發(fā)表于 2025-3-31 20:40:34 | 只看該作者
60#
發(fā)表于 2025-3-31 23:54:26 | 只看該作者
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