948 resultados para Error threshold


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The aim of this paper is the investigation of the error which results from the method of approximate approximations applied to functions defined on compact in- tervals, only. This method, which is based on an approximate partition of unity, was introduced by V. Mazya in 1991 and has mainly been used for functions defied on the whole space up to now. For the treatment of differential equations and boundary integral equations, however, an efficient approximation procedure on compact intervals is needed. In the present paper we apply the method of approximate approximations to functions which are defined on compact intervals. In contrast to the whole space case here a truncation error has to be controlled in addition. For the resulting total error pointwise estimates and L1-estimates are given, where all the constants are determined explicitly.

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Krypton atoms were excited by photons in the energy range from the threshold for photoionization of the 3d-electrons up to 120 eV. and the fluorescence radiation in the spectral range from 780 to 965 A was observed and analyzed. Cross sections for the population of excited states in KrIII with at least one 4s-hole resulting from an Auger transition as the first decay step and for KrII satellites were determined. The energy dependence of the 3d-ionization cross section in the 3d{_5/2}- and the 3d{_3/2}-threshold range was derived from the experimental data. The cross sections for production of KrII states were found to follow the energy dependence of the 3d-cross sections.

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The Kr 4s-electron photoionization cross section as a function of the exciting-photon energy in the range between 30 eV and 90 eV was calculated using the configuration interaction (CI) technique in intermediate coupling. In the calculations the 4p spin-orbital interaction and corrections due to higher orders of perturbation theory (the so-called Coulomb interaction correlational decrease) were considered. Energies of Kr II states were calculated and agree with spectroscopic data within less than 10 meV. For some of the Kr II states new assignments were suggested on the basis of the largest component among the calculated CI wavefunctions.

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The photoionization cross sections for the production of the Kr II 4s state and Kr II satellite states were studied in the 4s ionization threshold region. The interference of direct photoionization and ionization through the autoionization decay of doubly-excited states was considered. In the calculations of doubly-excited state energies, performed by a configuration interaction technique, the 4p spin-orbit interaction and the (Kr II core)-(excited electron) Coulomb interaction were included. The theoretical cross sections are in many cases in good agreement with the measured values. Strong resonant features in the satellite spectra with threshold energies greater than 30 eV are predicted.

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The photoionization of the Ne 2s-electrons was studied from threshold to 1 eV above threshold. The technique of photon-induced fluorescence spectroscopy was applied. Pronounced structures were observed resulting from autoionization of doubly excited atomic states. A threshold cross section of 0.17 Mb was determined.

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Absolute cross sections for the transitions of the Kr atom into the 4s^1 and 4p^4nl states of the Kr^+ ion were measured in the 4s-electron threshold region by photon-induced fluorescence spectroscopy (PIFS). The cross sections for the transitions of the Kr atom into the 4s^1 and 4p^4nl states were also calculated, as well as the 4p^4nln'l' doubly excited states, in the frame of LS-coupling many-body technique. The cross sections of the doubly-excited atomic states were used to illustrate the pronounced contributions of the latter to the photoionization process, evident from the measurements. The comparison of theory and experiment led to conclusions about the origin of the main features observed in the experiment.

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In the collision system Xe - Ag, the thresholds for excitation of quasimolecular L radiation and characteristic Ag L radiation have been found to lie at about 5 MeV and 1 MeV, respectively. These results are discussed on the basis of ab initio calculations of the screened interaction potential and the electron-correlation diagram.

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The aim of this paper is the numerical treatment of a boundary value problem for the system of Stokes' equations. For this we extend the method of approximate approximations to boundary value problems. This method was introduced by V. Maz'ya in 1991 and has been used until now for the approximation of smooth functions defined on the whole space and for the approximation of volume potentials. In the present paper we develop an approximation procedure for the solution of the interior Dirichlet problem for the system of Stokes' equations in two dimensions. The procedure is based on potential theoretical considerations in connection with a boundary integral equations method and consists of three approximation steps as follows. In a first step the unknown source density in the potential representation of the solution is replaced by approximate approximations. In a second step the decay behavior of the generating functions is used to gain a suitable approximation for the potential kernel, and in a third step Nyström's method leads to a linear algebraic system for the approximate source density. For every step a convergence analysis is established and corresponding error estimates are given.

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Object recognition is complicated by clutter, occlusion, and sensor error. Since pose hypotheses are based on image feature locations, these effects can lead to false negatives and positives. In a typical recognition algorithm, pose hypotheses are tested against the image, and a score is assigned to each hypothesis. We use a statistical model to determine the score distribution associated with correct and incorrect pose hypotheses, and use binary hypothesis testing techniques to distinguish between them. Using this approach we can compare algorithms and noise models, and automatically choose values for internal system thresholds to minimize the probability of making a mistake.

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The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

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In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression

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Several methods have been suggested to estimate non-linear models with interaction terms in the presence of measurement error. Structural equation models eliminate measurement error bias, but require large samples. Ordinary least squares regression on summated scales, regression on factor scores and partial least squares are appropriate for small samples but do not correct measurement error bias. Two stage least squares regression does correct measurement error bias but the results strongly depend on the instrumental variable choice. This article discusses the old disattenuated regression method as an alternative for correcting measurement error in small samples. The method is extended to the case of interaction terms and is illustrated on a model that examines the interaction effect of innovation and style of use of budgets on business performance. Alternative reliability estimates that can be used to disattenuate the estimates are discussed. A comparison is made with the alternative methods. Methods that do not correct for measurement error bias perform very similarly and considerably worse than disattenuated regression

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Resumen tomado de la publicaci??n

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Files used for and during the Threshold 1 workshop