935 resultados para Degree of contribution
Resumo:
We study the change in the degree of coherence of partially coherent electromagnetic beam (so called electromagnetic Gaussian Schell-model beam). It is shown analytically that with a fixed set of source parameters and under a particular atmospheric turbulence model, an electromagnetic Gaussian Schell-model beam propagating through atmospheric turbulence reaches its maximum value of coherence after the beam propagates a particular distance, and the effective width of the spectral degree of coherence also has its maximum value. This phenomenon is independent of the used turbulence model. The results are illustrated by numerical curves. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
Prior synaptic or cellular activity influences degree or threshold for subsequent induction of synaptic plasticity, a process known as metaplasticity. Thus, the continual synaptic activity, spontaneous miniature excitatory synaptic current (mEPSC) may correlate to the induction of long-teen depression (LTD). Here, we recorded whole-cell EPSC and mEPSC alternately in the Schaffer-CA1 synapses in brain slice of young rats, and found that this recording configuration affected neither EPSC nor mEPSC. Low frequency stimulation (LFS) induced variable magnitudes of LTD. Remarkably, larger magnitudes of LTD were significantly correlated to smaller amplitude/lower frequency of the basal mEPSC. Furthermore, under the conditions reduced amplitude/frequency of the basal mEPSC by exposure to behavioral stress immediately before slice preparation or low concentration of calcium in bath solution, the magnitudes of LTD were still inversely correlated to mEPSC amplitude/frequency. These new findings suggest that spontaneous mEPSC may reflect functional and/or structural aspects of the synapses, the synaptic history ongoing metaplasticity. (C) 2005 Elsevier B.V. All rights reserved.
Resumo:
Photon quantum statistics of light can be shown by the high-order coherence. The fourth-order coherences of various quantum states including Pock states, coherent states, thermal states and squeezed vacuum states are investigated based on a double Banbury Brown Twiss (HBT) scheme. The analytical results are obtained by taking the overall efficiency and background into account.
Resumo:
We study the entanglement degree of electron pairs emitted from an s-wave Superconductor, which Couples to two normal leads via a single-level quantum dot. Within the framework of scattering matrix theory. the concurrence is used to quantify the entanglement. And the result shows that the entanglement degree is generally influenced by the initial separation of the two electrons in a Cooper pair and the normal transmission eigenvalues T-1, T-2. But it is only determined by the eigenvalues in the tunnelling limit, T-1. T-2 << 1, what is more. it is measurable. (C) 2008 Elsevier B.V. All rights reserved.
Resumo:
The strain state of 570nm AlXGa1-xN layers grown on 600nm GaN template by metal organic chemical vapor deposition was studied using Rutherford backscattering (RBS)/channeling and triple-axis X-ray diffraction measurements. The results showed that the degree of relaxation (R) of AlxGa1-xN layers increased almost linearly when x less than or equal to 0.42 and reached to 70% when x = 0.42. Above 0.42, the value of R varied slowly and AI(x)Ga(1-x)N layers almost full relaxed when x = 1 (AIN). In this work the underlying GaN layer was in compressive strain, which resulted in the reduction of lattice misfit between GaN and AlxGa1-xN, and a 570nm AlxGa1-xN layer with the composition of about 0.16 might be grown on GaN coherently from the extrapolation. The different shape of (0004) diffraction peak was discussed to be related to the relaxation. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
In this paper, we study a problem of geometric inequalities for a Multi-degree of Freedom Neurons. Some new geometric inequalities for a Multi-degree of Freedom Neurons are established. As special cases, some known inequalities are deduced.
Resumo:
In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.
Resumo:
An algorithm of PCA face recognition based on Multi-degree of Freedom Neurons theory is proposed, which based on the sample sets' topological character in the feature space which is different from "classification". Compare with the traditional PCA+NN algorithm, experiments prove its efficiency.
Resumo:
In this paper, we redefine the sample points set in the feature space from the point of view of weighted graph and propose a new covering model - Multi-Degree-of-Freedorn Neurons (MDFN). Base on this model, we describe a geometric learning algorithm with 3-degree-of-freedom neurons. It identifies the sample points secs topological character in the feature space, which is different from the traditional "separation" method. Experiment results demonstrates the general superiority of this algorithm over the traditional PCA+NN algorithm in terms of efficiency and accuracy.