619 research outputs found

    Nonasymptotic analysis of adaptive and annealed Feynman-Kac particle models

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    Sequential and quantum Monte Carlo methods, as well as genetic type search algorithms can be interpreted as a mean field and interacting particle approximations of Feynman-Kac models in distribution spaces. The performance of these population Monte Carlo algorithms is strongly related to the stability properties of nonlinear Feynman-Kac semigroups. In this paper, we analyze these models in terms of Dobrushin ergodic coefficients of the reference Markov transitions and the oscillations of the potential functions. Sufficient conditions for uniform concentration inequalities w.r.t. time are expressed explicitly in terms of these two quantities. We provide an original perturbation analysis that applies to annealed and adaptive Feynman-Kac models, yielding what seems to be the first results of this kind for these types of models. Special attention is devoted to the particular case of Boltzmann-Gibbs measures' sampling. In this context, we design an explicit way of tuning the number of Markov chain Monte Carlo iterations with temperature schedule. We also design an alternative interacting particle method based on an adaptive strategy to define the temperature increments. The theoretical analysis of the performance of this adaptive model is much more involved as both the potential functions and the reference Markov transitions now depend on the random evolution on the particle model. The nonasymptotic analysis of these complex adaptive models is an open research problem. We initiate this study with the concentration analysis of a simplified adaptive models based on reference Markov transitions that coincide with the limiting quantities, as the number of particles tends to infinity.Comment: Published at http://dx.doi.org/10.3150/14-BEJ680 in the Bernoulli (http://isi.cbs.nl/bernoulli/) by the International Statistical Institute/Bernoulli Society (http://isi.cbs.nl/BS/bshome.htm

    Aggregation of predictors for nonstationary sub-linear processes and online adaptive forecasting of time varying autoregressive processes

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    In this work, we study the problem of aggregating a finite number of predictors for nonstationary sub-linear processes. We provide oracle inequalities relying essentially on three ingredients: (1) a uniform bound of the â„“1\ell^1 norm of the time varying sub-linear coefficients, (2) a Lipschitz assumption on the predictors and (3) moment conditions on the noise appearing in the linear representation. Two kinds of aggregations are considered giving rise to different moment conditions on the noise and more or less sharp oracle inequalities. We apply this approach for deriving an adaptive predictor for locally stationary time varying autoregressive (TVAR) processes. It is obtained by aggregating a finite number of well chosen predictors, each of them enjoying an optimal minimax convergence rate under specific smoothness conditions on the TVAR coefficients. We show that the obtained aggregated predictor achieves a minimax rate while adapting to the unknown smoothness. To prove this result, a lower bound is established for the minimax rate of the prediction risk for the TVAR process. Numerical experiments complete this study. An important feature of this approach is that the aggregated predictor can be computed recursively and is thus applicable in an online prediction context.Comment: Published at http://dx.doi.org/10.1214/15-AOS1345 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

    Di-boson results at ATLAS

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    Pairs of gauge boson produced in proton-proton collisions at a center-of-mass energy s\sqrt{s} of 7 TeV are reconstructed with the ATLAS detector in their leptonic final states. Based on samples of integrated luminosity L=1.0fb−1L=1.0 fb^{-1} (for WW, WZ and ZZ) and 35pb−135 pb^{-1} (for W\gamma and Z\gamma) of 2011 and 2010 LHC data, the total di-boson production cross sections are measured. They are found, together with the kinematic distributions of the selected di-boson systems to be compatible with the expectation from the Standard Model. The di-boson production also gives a handle on possible anomalous triple gauge boson couplings, for which 95% confidence limits are set.Comment: Presented at the 2011 Hadron Collider Physics symposium (HCP-2011), Paris, France, November 14-18 2011, 4 pages, 7 figure

    Experimental Study of Iron Losses Generated by a Uniform Rotating Field

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    This paper introduces a mock-up with a solid iron cylinder rotating in a fixed excitation frame powered by dc current. A uniform field is created in the rotating cylinder, which is driven by an external motor. The braking torque is measured, allowing the study of iron losses generated by a uniform rotating field. The aim is to advance toward a vector iron loss model that takes into account different magnetization directions and their interdependency. The eddy current losses are the dominant loss source in the mock-up, rendering it easier to model. A standard eddy currents model is proposed. It models well the losses at low and medium magnetic flux density, but lower losses are measured near saturation levels. This could be due to the high thickness to radius ratio changing the eddy current paths near the edges of the rotor, which can be later analyzed by a full 3-D finite-element method analysis. A 2-D finite-element method simulation is performed, which estimates the magnetic flux heterogeneity in the rotor. Several lessons are drawn from this mock-up, which prepares a second version with a higher speed and a longer laminated stack rotor. A higher air gap will decrease the voltage fluctuation in the primary winding, a smaller angular opening of the excitation frame will improve the uniformity of the flux in the rotor

    Modeling quasi-static magnetic hysteresis: a new implementation of the play model based on experimental asymmetrical B(H) loops

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    This paper relates a new model of quasi-static magnetic hysteresis based on the Play model hysterons, which builds the magnetic field density B from the magnetic field H. In the original model, H is discretized into temporal values H(t m ), which is itself modeled by a hysteron chain of m sub-values. B is then reconstructed from these sub-values through a function experimentally determined by measuring B(H) centered cycles, using a constraint optimization method. The new proposed method is to measure asymmetrical B(H) loops, which give additional equations leading to a fully determined linear square invertible system. The asymmetrical B(H) loop is included in a bigger symmetrical loop with a magnetic flux density turnaround in order to be regulatable

    Avant-propos

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    Considérée depuis l’époque moderne et son historiographie contemporaine, l’étude de la « langue mystique » comme voie d’accès privilégiée à la mystique est un acquis. Les travaux de Michel de Certeau ont ainsi montré que l’apparition de la mystique en tant que substantif, au début du xviie siècle, correspondait à une affirmation stylistique nette : il existe une langue propre aux mystiques, qui s’autorise d’une expérience, à un moment et en un lieu déterminés. Cette autonomisation de la mysti..

    Automatic 3D seed location and orientation in CT images for prostate brachytherapy

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    International audienceIn prostate brachytherapy, the analysis of the 3D pose information of each individual implanted seed is one of the critical issues for dose calculation and procedure quality assessment. This paper addresses the development of an automatic image processing solution for the separation, localization and 3D orientation estimation of prostate seeds. This solution combines an initial detection of a set of seed candidates in CT images (using a thresholding and connected component method) with an orientation estimation using principal components analysis (PCA). The main originality of the work is the ability to classify the detected objects based on a priori intensity and volume information and to separate groups of seeds using a modified k-means method. Experiments were carried out on CT images of a phantom and a patient aiming to compare the proposed solution with manual segmentation or other previous work in terms of detection performance and calculation time
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