منابع مشابه
Predicting Periodic Phenomena with Self-Organising Maps
Self-Organising Maps are a form of neural network allowing unsupervised learning. In this work, we use a 2-dimensional network. Given a set of data, the neural network learns the distribution of data points, and provides a mapping from the set of data points to the neural network. The mapping has the property that similar data points map to nearby neurons in the network. Figure 2. Self-Organisi...
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1 Faculté des Sciences de Base, Ecole Polytechnique Fédérale de Lausanne, Institut de Physique de la Matière Condensée, Lausanne, Switzerland 2 Key Laboratory for Physics and Chemistry of Nanodevices and Department of Electronics, Peking University, Beijing, China 3 Institut des Nanosciences de Paris, Université Pierre et Marie Curie and CNRS-UMR 7588, Paris, France 4 Department of Chemical Phy...
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Extensive obscrvations wcre made on airing soundings, as are other characteristic cloud structures. craft flights in the marine layer over the Pacific Ocean From photographs of glories in the stratus tops, angles of off thc coast of southern California. We intcrpret somc of back-scattering can be dctcrmined with sufficient accuracy the cloud patterns as convective and some as gravity wave to id...
متن کاملBorder-collision bifurcations: An explanation for observed bifurcation phenomena.
Recently physical and computer experiments involving systems describable by continuous maps that are nondi8'erentiable on some surface in phase space have revealed novel bifurcation phenomena. These phenomena are part of a rich new class of bifurcations which we call border collisi-on bifurcations A. general criterion for the occurrence of border-collision bifurcations is given. Illustrative nu...
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ژورنال
عنوان ژورنال: International Astronomical Union Colloquium
سال: 2000
ISSN: 0252-9211
DOI: 10.1017/s0252921100055809