926 resultados para Gaussian convolution
Resumo:
It is shown that the families of generalized matrix ensembles recently considered which give rise to an orthogonal invariant stable Levy ensemble can be generated by the simple procedure of dividing Gaussian matrices by a random variable. The nonergodicity of this kind of disordered ensembles is investigated. It is shown that the same procedure applied to random graphs gives rise to a family that interpolates between the Erdos-Renyi and the scale free models.
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Gas aggregation is a well known method used to produce clusters of different materials with good size control, reduced dispersion, and precise stoichiometry. The cost of these systems is relatively high and they are generally dedicated apparatuses. Furthermore, the usual sample production speed of these systems is not as fast as physical vapor deposition devices posing a problem when thick samples are needed. In this paper we describe the development of a multipurpose gas aggregation system constructed as an adaptation to a magnetron sputtering system. The cost of this adaptation is negligible and its installation and operation are both remarkably simple. The gas flow for flux in the range of 60-130 SCCM (SCCM denotes cubic centimeter per minute at STP) is able to completely collimate all the sputtered material, producing spherical nanoparticles. Co nanoparticles were produced and characterized using electron microscopy techniques and Rutherford back-scattering analysis. The size of the particles is around 10 nm with around 75 nm/min of deposition rate at the center of a Gaussian profile nanoparticle beam.
Resumo:
Online music databases have increased significantly as a consequence of the rapid growth of the Internet and digital audio, requiring the development of faster and more efficient tools for music content analysis. Musical genres are widely used to organize music collections. In this paper, the problem of automatic single and multi-label music genre classification is addressed by exploring rhythm-based features obtained from a respective complex network representation. A Markov model is built in order to analyse the temporal sequence of rhythmic notation events. Feature analysis is performed by using two multi-variate statistical approaches: principal components analysis (unsupervised) and linear discriminant analysis (supervised). Similarly, two classifiers are applied in order to identify the category of rhythms: parametric Bayesian classifier under the Gaussian hypothesis (supervised) and agglomerative hierarchical clustering (unsupervised). Qualitative results obtained by using the kappa coefficient and the obtained clusters corroborated the effectiveness of the proposed method.
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The transition of plasmons from propagating to localized state was studied in disordered systems formed in GaAs/AlGaAs superlattices by impurities and by artificial random potential. Both the localization length and the linewidth of plasmons were measured by Raman scattering. The vanishing dependence of the plasmon linewidth on the disorder strength was shown to be a manifestation of the strong plasmon localization. The theoretical approach based on representation of the plasmon wave function in a Gaussian form well accounted for by the obtained experimental data.
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The influence of interlayer coupling on the formation of the quantized Hall phase at the filling factor nu=2 was studied in multilayer GaAs/AlGaAs heterostructures. The disorder broadened Gaussian photoluminescence line due to localized electrons was found in the quantized Hall phase of the isolated multi-quanturn-well structure. On the other hand, the quantized Hall phase of weakly coupled multilayers emitted an unexpected asymmetrical line similar to that observed in metallic electron systems. We demonstrated that the observed asymmetry is caused by the partial population of extended electron states formed in the insulating quantized Hall phase due to spin-assisted interlayer percolation. A sharp decrease in the single-particle scattering time associated with these extended states was observed for the filling factor nu=2. (C) 2008 American Institute of Physics. [DOI: 10.1063/1.2978194]
Resumo:
Measured and calculated differential cross sections for elastic (rotationally unresolved) electron scattering from two primary alcohols, methanol (CH(3)OH) and ethanol (C(2)H(5)OH), are reported. The measurements are obtained using the relative flow method with helium as the standard gas and a thin aperture as the collimating target gas source. The relative flow method is applied without the restriction imposed by the relative flow pressure conditions on helium and the unknown gas. The experimental data were taken at incident electron energies of 1, 2, 5, 10, 15, 20, 30, 50, and 100 eV and for scattering angles of 5 degrees-130 degrees. There are no previous reports of experimental electron scattering differential cross sections for CH(3)OH and C(2)H(5)OH in the literature. The calculated differential cross sections are obtained using two different implementations of the Schwinger multichannel method, one that takes all electrons into account and is adapted for parallel computers, and another that uses pseudopotentials and considers only the valence electrons. Comparison between theory and experiment shows that theory is able to describe low-energy electron scattering from these polyatomic targets quite well.
Resumo:
The doubly positively charged gas-phase molecules BrO(2+) and NBr(2+) have been produced by prolonged high-current energetic oxygen (17 keV (16)O(-)) ion surface bombardment (ion beam sputtering) of rubidium bromide (RbBr) and of ammonium bromide (NH(4)Br) powdered ionic salt samples, respectively, pressed into indium foil. These novel species were observed at half-integer m/z values in positive ion mass spectra for ion flight times of roughly similar to 12 mu s through a magnetic-sector secondary ion mass spectrometer. Here we present these experimental results and combine them with a detailed theoretical investigation using high level ab initio calculations of the ground states of BrO(2+) and NBr(2+), and a manifold of excited electronic states. NBr(2+) and BrO(2+), in their ground states, are long-lived metastable gas-phase molecules with well depths of 2.73 x 10(4) cm(-1) (3.38 eV) and 1.62 x 10(4) cm(-1) (2.01 eV); their fragmentation channels into two monocations lie 2.31 x 10(3) cm(-1) (0.29 eV) and 2.14 x 10(4) cm(-1) (2.65 eV) below the ground state minimum. The calculated lifetimes for NBr(2+) (v '' < 35) and BrO(2+) (v '' < 18) are large enough to be considered stable against tunneling. For NBr(2+), we predicted R(e) = 3.051 a(0) and omega(e) = 984 cm(-1); for BrO(2+), we obtained 3.033 a(0) and 916 cm(-1), respectively. The adiabatic double ionization energies of BrO and NBr to form metastable BrO(2+) and NBr(2+) are calculated to be 30.73 and 29.08 eV, respectively. The effect of spin-orbit interactions on the low-lying (Lambda + S) states is also discussed. (C) 2011 American Institute of Physics. [doi:10.1063/1.3562121]
Resumo:
The low-lying doublet and quartet electronic states of the species SeF correlating with the first dissociation channel are investigated theoretically at a high-level of electronic correlation treatment, namely, the complete active space self-consistent field/multireference single and double excitations configuration interaction (CASSCF/MRSDCI) using a quintuple-zeta quality basis set including a relativistic effective core potential for the selenium atom. Potential energy curves for (Lambda+S) states and the corresponding spectroscopic properties are derived that allows for an unambiguous assignment of the only spectrum known experimentally as due to a spin-forbidden X (2)Pi-a (4)Sigma(-) transition, and not a A (2)Pi-X (2)Pi transition as assumed so far. For the bound excited doublets, yet unknown experimentally, this study is the first theoretical characterization of their spectroscopic properties. Also the spin-orbit coupling constant function for the X (2)Pi state is derived as well as the spin-orbit coupling matrix element between the X (2)Pi and a (4)Sigma(-) states. Dipole moment functions and vibrationally averaged dipole moments show SeF to be a very polar species. An overview of the lowest-lying spin-orbit (Omega) states completes this description. (C) 2010 American Institute of Physics. [doi: 10.1063/1.3426315]
Resumo:
We have investigated the stability, electronic properties, Rayleigh (elastic), and Raman (inelastic) depolarization ratios, infrared and Raman absorption vibrational spectra of fullerenols [C(60)(OH)(n)] with different degrees of hydroxylation by using all-electron density-functional-theory (DFT) methods. Stable arrangements of these molecules were found by means of full geometry optimizations using Becke's three-parameter exchange functional with the Lee, Yang, and Parr correlation functional. This DFT level has been combined with the 6-31G(d,p) Gaussian-type basis set, as a compromise between accuracy and capability to treat highly hydroxylated fullerenes, e.g., C(60)(OH)(36). Thus, the molecular properties of fullerenols were systematically analyzed for structures with n=1, 2, 3, 4, 8, 10, 16, 18, 24, 32, and 36. From the electronic structure analysis of these molecules, we have evidenced an important effect related to the weak chemical reactivity of a possible C(60)(OH)(24) isomer. To investigate Raman scattering and the vibrational spectra of the different fullerenols, frequency calculations are carried out within the harmonic approximation. In this case a systematic study is only performed for n=1-4, 8, 10, 16, 18, and 24. Our results give good agreements with the expected changes in the spectral absorptions due to the hydroxylation of fullerenes.
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Objective: We carry out a systematic assessment on a suite of kernel-based learning machines while coping with the task of epilepsy diagnosis through automatic electroencephalogram (EEG) signal classification. Methods and materials: The kernel machines investigated include the standard support vector machine (SVM), the least squares SVM, the Lagrangian SVM, the smooth SVM, the proximal SVM, and the relevance vector machine. An extensive series of experiments was conducted on publicly available data, whose clinical EEG recordings were obtained from five normal subjects and five epileptic patients. The performance levels delivered by the different kernel machines are contrasted in terms of the criteria of predictive accuracy, sensitivity to the kernel function/parameter value, and sensitivity to the type of features extracted from the signal. For this purpose, 26 values for the kernel parameter (radius) of two well-known kernel functions (namely. Gaussian and exponential radial basis functions) were considered as well as 21 types of features extracted from the EEG signal, including statistical values derived from the discrete wavelet transform, Lyapunov exponents, and combinations thereof. Results: We first quantitatively assess the impact of the choice of the wavelet basis on the quality of the features extracted. Four wavelet basis functions were considered in this study. Then, we provide the average accuracy (i.e., cross-validation error) values delivered by 252 kernel machine configurations; in particular, 40%/35% of the best-calibrated models of the standard and least squares SVMs reached 100% accuracy rate for the two kernel functions considered. Moreover, we show the sensitivity profiles exhibited by a large sample of the configurations whereby one can visually inspect their levels of sensitiveness to the type of feature and to the kernel function/parameter value. Conclusions: Overall, the results evidence that all kernel machines are competitive in terms of accuracy, with the standard and least squares SVMs prevailing more consistently. Moreover, the choice of the kernel function and parameter value as well as the choice of the feature extractor are critical decisions to be taken, albeit the choice of the wavelet family seems not to be so relevant. Also, the statistical values calculated over the Lyapunov exponents were good sources of signal representation, but not as informative as their wavelet counterparts. Finally, a typical sensitivity profile has emerged among all types of machines, involving some regions of stability separated by zones of sharp variation, with some kernel parameter values clearly associated with better accuracy rates (zones of optimality). (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
Here, I investigate the use of Bayesian updating rules applied to modeling how social agents change their minds in the case of continuous opinion models. Given another agent statement about the continuous value of a variable, we will see that interesting dynamics emerge when an agent assigns a likelihood to that value that is a mixture of a Gaussian and a uniform distribution. This represents the idea that the other agent might have no idea about what is being talked about. The effect of updating only the first moments of the distribution will be studied, and we will see that this generates results similar to those of the bounded confidence models. On also updating the second moment, several different opinions always survive in the long run, as agents become more stubborn with time. However, depending on the probability of error and initial uncertainty, those opinions might be clustered around a central value.
Resumo:
A study on the possible sites of oxidation and epoxidation of nortriptyline was performed using electrochemical and quantum chemical methods; these sites are involved in the biological responses (for example, hepatotoxicity) of nortriptyline and other similar antidepressants. Quantum chemical studies and electrochemical experiments demonstrated that the oxidation and epoxidation sites are located on the apolar region of nortriptyline, which will useful for understanding the molecule`s activity. Also, for the determination of the compound in biological fluids or in pharmaceutical formulations, we propose a useful analytical methodology using a graphite-polyurethane composite electrode, which exhibited the best performance when compared with boron-doped diamond or glassy carbon surfaces.
Resumo:
We show that commutative group spherical codes in R(n), as introduced by D. Slepian, are directly related to flat tori and quotients of lattices. As consequence of this view, we derive new results on the geometry of these codes and an upper bound for their cardinality in terms of minimum distance and the maximum center density of lattices and general spherical packings in the half dimension of the code. This bound is tight in the sense it can be arbitrarily approached in any dimension. Examples of this approach and a comparison of this bound with Union and Rankin bounds for general spherical codes is also presented.
Resumo:
This paper proposes a novel computer vision approach that processes video sequences of people walking and then recognises those people by their gait. Human motion carries different information that can be analysed in various ways. The skeleton carries motion information about human joints, and the silhouette carries information about boundary motion of the human body. Moreover, binary and gray-level images contain different information about human movements. This work proposes to recover these different kinds of information to interpret the global motion of the human body based on four different segmented image models, using a fusion model to improve classification. Our proposed method considers the set of the segmented frames of each individual as a distinct class and each frame as an object of this class. The methodology applies background extraction using the Gaussian Mixture Model (GMM), a scale reduction based on the Wavelet Transform (WT) and feature extraction by Principal Component Analysis (PCA). We propose four new schemas for motion information capture: the Silhouette-Gray-Wavelet model (SGW) captures motion based on grey level variations; the Silhouette-Binary-Wavelet model (SBW) captures motion based on binary information; the Silhouette-Edge-Binary model (SEW) captures motion based on edge information and the Silhouette Skeleton Wavelet model (SSW) captures motion based on skeleton movement. The classification rates obtained separately from these four different models are then merged using a new proposed fusion technique. The results suggest excellent performance in terms of recognising people by their gait.
Resumo:
A multiphase deterministic mathematical model was implemented to predict the formation of the grain macrostructure during unidirectional solidification. The model consists of macroscopic equations of energy, mass, and species conservation coupled with dendritic growth models. A grain nucleation model based on a Gaussian distribution of nucleation undercoolings was also adopted. At some solidification conditions, the cooling curves calculated with the model showed oscillations (""wiggles""), which prevented the correct prediction of the average grain size along the structure. Numerous simulations were carried out at nucleation conditions where the oscillations are absent, enabling an assessment of the effect of the heat transfer coefficient on the average grain size and columnar-to-equiaxed transition.