نتایج جستجو برای: ñ

تعداد نتایج: 579  

Journal: :Boletín de la Academia Peruana de la Lengua 2011

2008
Nicolas Bouleau Nicolas BOULEAU

We propose a new method to apply the Lipschitz functional calculus of local Dirichlet forms to Poisson random measures. Résumé Calcul d’erreur et régularité des fonctionnelles de Poisson : la méthode de la particule prêtée. Nous proposons une nouvelle méthode pour appliquer le calcul fonctionnel lipschitzien des formes de Dirichlet locales aux mesures aléatoires de Poisson. 1 Notation and basic...

2007
Ken-ichi Kondo Thomas J. Ahrens

Two shock wave experiments employing Lau• technique. The normal axis to the sample inclined mirrors have been carried out to surface of both crystals were very close to each determine the Hugoniot elastic limit (HEL), final other and inclined 15.4 ñ 0.6 ø from <111>, or 29.6 shock state at 191 and 217 GPa, and the post-shock ñ 0.6 ø from <110> in approximately the (110) state of diamond crystal...

2001
Francis F. Chen Pat Colestock P. L. Colestock

Known for their ability to produce high densities at low power, helicon discharges have found many practical uses. However, with light gases it has been found that the plasma density saturates, then falls, as the magnetic field is increased. This can be explained by the onset of a drift-type instability, whose threshold agrees well with linear theory. Measurements of radial and axial particle f...

2007
R. A. Mewaldt E. C. Stone R. E. Vogt

The spectra of both protons and alph'a pa•-ticles (1 <• E • 7 MeV/nucleon) during 31 recurrent particle streams are fit well by an exponential in particle rigidity. Although the spectra show considerable temporal variation, the proton and alpha particle spectra are correlated such that the e-folding rigidities Po(•) and Po(P) of the two spectra are in the ratio Po(•)/ Po(P) = 1.5 ñ 0.1. The con...

2017
Karl Ridgeway Michael C. Mozer

We propose and evaluate a novel loss function for discovering deep embeddings that make explicit the categorical and semantic structure of a domain. The loss function is based on the F statistic that describes the separation of two or more distributions. This loss has several key advantages over previous approaches, including: it does not require a margin or arbitrary parameters for determining...

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