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Such manifold increase in luminescence may be explained by the principles of plasmon coupling, directional emission led high collection efficiency, Rayleigh scattering and related opto-electronic events.
It is a work of such manifold characterisation and knotty scenarios that it could surely not have been written shorter or more quickly.
We show that by embedding the manifold into reproducing kernel Hilbert space and applying the mechanics of graph embedding on such manifold, significant performance improvement can be obtained.
Every such manifold carries a continuous biholomorphically invariant distance, and therefore if (Y) is Kobayashi-hyperbolic, then (mathrm{Bihol}(Y)) acts on (Y) properly.
The main result of [53] states that every such manifold is biholomorphic to a Reinhardt domain and hence the classification in this case is a subset of that in [30].
In consideration of the neighborhood structure manifold which exploits the relative relationship between the concerned samples and their neighbors in the feature space, we propose a novel method, "Neighborhood Structure Metric Learning", to learn discriminative dissimilarities on such manifold by adapting the codomain metrics of its charts.
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Very little was known about such manifolds, and, although the German mathematician Bernhard Riemann had hinted at them a generation or more earlier, few had taken the hint.
Poincaré took up the task and looked for ways in which such manifolds could be distinguished, thus opening up the whole subject of topology, then known as analysis situs.
Such manifolds M are called data bases.
A typical Hodgkin-Huxley model possesses a pair of such manifolds [4]: quiescent and tonic spiking.
We present a novel method for computing approximations of such manifolds using trajectory-based optimization.
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