The Experts below are selected from a list of 169395 Experts worldwide ranked by ideXlab platform
Hubert Preißl - One of the best experts on this subject based on the ideXlab platform.
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detection of uterine mmg contractions using a multiple change point estimator and the k means Cluster Algorithm
IEEE Transactions on Biomedical Engineering, 2008Co-Authors: P S La Rosa, Hari Eswaran, Curtis L Lowery, Arye Nehorai, Hubert PreißlAbstract:We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-point detection in each stage of the binary search Algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means Cluster Algorithm to classify the detected time segments using the RMS values. We apply our detection Algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection Algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach.
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detection of uterine mmg contractions using a multiple change point estimator and k means Cluster Algorithm
International Congress Series, 2007Co-Authors: P S La Rosa, Hari Eswaran, Curtis L Lowery, Hubert Preißl, Arye NehoraiAbstract:Abstract We propose a single-channel two-stage detector of uterine magnetomyogram (MMG) contractions during pregnancy. In the first stage, we assume that the measurements are modeled by a zero-mean Gaussian random variable with time-varying piecewise constant variance. Therefore, we apply a model-based segmentation procedure which detects multiple change points in the variance values using the Schwarz information criterion (SIC) and a binary search approach. Then, in the second stage, we apply the K -means Cluster Algorithm to classify each time segment using the root-mean square (RMS) as a feature. We apply our Algorithm to real MMG records obtained from five patients having contractions with gestational ages between 31 and 40 weeks.
Martin Hasenbusch - One of the best experts on this subject based on the ideXlab platform.
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variance reduced estimator of the connected two point function in the presence of a broken z 2 symmetry
Physical Review E, 2016Co-Authors: Martin HasenbuschAbstract:The exchange or geometric Cluster Algorithm allows us to define a variance reduced estimator of the connected two-point function in the presence of a broken Z2-symmetry. We present first numerical tests for the improved Blume-Capel model on the simple cubic lattice. We perform simulations for the critical isotherm, the low temperature phase at vanishing external field and, for comparison, also the high temperature phase. For the connected two-point function a substantial *� � �
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Thermodynamic Casimir effect in films: the exchange Cluster Algorithm.
Physical Review E, 2015Co-Authors: Martin HasenbuschAbstract:We study the thermodynamic Casimir force for films with various types of boundary conditions and the bulk universality class of the three-dimensional Ising model. To this end, we perform Monte Carlo simulations of the improved Blume-Capel model on the simple cubic lattice. In particular, we employ the exchange or geometric Cluster Cluster Algorithm [Heringa and Blote, Phys. Rev. E 57, 4976 (1998)]. In a previous work, we demonstrated that this Algorithm allows us to compute the thermodynamic Casimir force for the plate-sphere geometry efficiently. It turns out that also for the film geometry a substantial reduction of the statistical error can achieved. Concerning physics, we focus on (O,O) boundary conditions, where O denotes the ordinary surface transition. These are implemented by free boundary conditions on both sides of the film. Films with such boundary conditions undergo a phase transition in the universality class of the two-dimensional Ising model. We determine the inverse transition temperature for a large range of thicknesses L(0) of the film and study the scaling of this temperature with L(0). In the neighborhood of the transition, the thermodynamic Casimir force is affected by finite size effects, where finite size refers to a finite transversal extension L of the film. We demonstrate that these finite size effects can be computed by using the universal finite size scaling function of the free energy of the two-dimensional Ising model.
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Direct Monte Carlo measurement of the surface tension in Ising models
Journal de Physique I, 1993Co-Authors: Martin HasenbuschAbstract:I present a Cluster Monte Carlo Algorithm that gives direct access to the interface free energy of Ising models. The basic idea is to simulate an ensemble that consists of both configurations with periodic and with antiperiodic boundary conditions. A Cluster Algorithm is provided that efficiently updates this joint ensemble. The interface tension is obtained from the ratio of configurations with periodic and antiperiodic boundary conditions, respectively. The method is tested for the 3-dimensional Ising model.
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High precision measurement of the SOS surface thickness in the rough phase
Journal de Physique I, 1991Co-Authors: Hans Gerd Evertz, Martin Hasenbusch, Mihail Marcu, Klaus Pinn, Sorin SolomonAbstract:Using a Cluster Algorithm without critical slowing down for the discrete Gaussian SOS model, we verify to high precision the linear dependence of the surface thickness on the logarithm of the lattice size.
P S La Rosa - One of the best experts on this subject based on the ideXlab platform.
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detection of uterine mmg contractions using a multiple change point estimator and the k means Cluster Algorithm
IEEE Transactions on Biomedical Engineering, 2008Co-Authors: P S La Rosa, Hari Eswaran, Curtis L Lowery, Arye Nehorai, Hubert PreißlAbstract:We propose a single channel two-stage time-segment discriminator of uterine magnetomyogram (MMG) contractions during pregnancy. We assume that the preprocessed signals are piecewise stationary having distribution in a common family with a fixed number of parameters. Therefore, at the first stage, we propose a model-based segmentation procedure, which detects multiple change-points in the parameters of a piecewise constant time-varying autoregressive model using a robust formulation of the Schwarz information criterion (SIC) and a binary search approach. In particular, we propose a test statistic that depends on the SIC, derive its asymptotic distribution, and obtain closed-form optimal detection thresholds in the sense of the Neyman-Pearson criterion; therefore, we control the probability of false alarm and maximize the probability of change-point detection in each stage of the binary search Algorithm. We compute and evaluate the relative energy variation [root mean squares (RMS)] and the dominant frequency component [first order zero crossing (FOZC)] in discriminating between time segments with and without contractions. The former consistently detects a time segment with contractions. Thus, at the second stage, we apply a nonsupervised K-means Cluster Algorithm to classify the detected time segments using the RMS values. We apply our detection Algorithm to real MMG records obtained from ten patients admitted to the hospital for contractions with gestational ages between 31 and 40 weeks. We evaluate the performance of our detection Algorithm in computing the detection and false alarm rate, respectively, using as a reference the patients' feedback. We also analyze the fusion of the decision signals from all the sensors as in the parallel distributed detection approach.
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detection of uterine mmg contractions using a multiple change point estimator and k means Cluster Algorithm
International Congress Series, 2007Co-Authors: P S La Rosa, Hari Eswaran, Curtis L Lowery, Hubert Preißl, Arye NehoraiAbstract:Abstract We propose a single-channel two-stage detector of uterine magnetomyogram (MMG) contractions during pregnancy. In the first stage, we assume that the measurements are modeled by a zero-mean Gaussian random variable with time-varying piecewise constant variance. Therefore, we apply a model-based segmentation procedure which detects multiple change points in the variance values using the Schwarz information criterion (SIC) and a binary search approach. Then, in the second stage, we apply the K -means Cluster Algorithm to classify each time segment using the root-mean square (RMS) as a feature. We apply our Algorithm to real MMG records obtained from five patients having contractions with gestational ages between 31 and 40 weeks.
Hans Gerd Evertz - One of the best experts on this subject based on the ideXlab platform.
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A NONLOCAL APPROACH TO VERTEX MODELS AND QUANTUM SPIN SYSTEMS
International Journal of Modern Physics C, 1993Co-Authors: Hans Gerd Evertz, Mihai MarcuAbstract:We discuss the loop-Algorithm, a new type of Cluster Algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop Algorithm. We show how to modify the original Algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions, and we discuss parallelization.
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Vertex Models and Quantum-Spin Systems: A Nonlocal Approach
arXiv: Condensed Matter, 1993Co-Authors: Hans Gerd Evertz, Mihai MarcuAbstract:Within a general Cluster framework, we discuss the loop-Algorithm, a new type of Cluster Algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop Algorithm. We discuss how to modify the original Algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions.
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Cluster Algorithm for vertex models
Physical Review Letters, 1993Co-Authors: Hans Gerd Evertz, Gideon Lana, Mihai MarcuAbstract:We present a new type of Cluster Algorithm that strongly reduces critical slowing down in simulations of vertex models. Since the Clusters are closed paths of bonds, we call it the loop Algorithm. The basic steps in constructing a Cluster are the breakup and the freezing of vertices. We concentrate on the case of the F model, which is a subset of the six-vertex model exhibiting a Kosterlitz-Thouless transition. The loop Algorithm is also applicable to simulations of other vertex models and of one- and two-dimensional quantum spin systems
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Critical acceleration of finite-temperature SU(2) gauge simulations.
Physical Review D, 1991Co-Authors: Radel Ben-av, Hans Gerd Evertz, Mihail Marcu, Sorin SolomonAbstract:We present a Cluster Algorithm that strongly reduces critical slowing down for the SU(2) gauge theory on one time slice. The idea that underlies the new Algorithm is to perform efficient flips for the signs of Polyakov loops. Ergodicity is ensured by combining it with a standard local Algorithm. We show how to quantify critical slowing down for such a mixed Algorithm. At the finite-temperature transition, the dynamical critical exponent {ital z} is {approx}0.5, whereas the purely local Algorithm {ital z}{approx}2.
Mihai Marcu - One of the best experts on this subject based on the ideXlab platform.
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A NONLOCAL APPROACH TO VERTEX MODELS AND QUANTUM SPIN SYSTEMS
International Journal of Modern Physics C, 1993Co-Authors: Hans Gerd Evertz, Mihai MarcuAbstract:We discuss the loop-Algorithm, a new type of Cluster Algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop Algorithm. We show how to modify the original Algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions, and we discuss parallelization.
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Vertex Models and Quantum-Spin Systems: A Nonlocal Approach
arXiv: Condensed Matter, 1993Co-Authors: Hans Gerd Evertz, Mihai MarcuAbstract:Within a general Cluster framework, we discuss the loop-Algorithm, a new type of Cluster Algorithm that reduces critical slowing down in vertex models and in quantum spin systems. We cover the example of the 6-vertex model in detail. For the F-model, we present numerical results that demonstrate the effectiveness of the loop Algorithm. We discuss how to modify the original Algorithm for some more complicated situations, especially for quantum spin systems in one and two dimensions.
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Cluster Algorithm for vertex models
Physical Review Letters, 1993Co-Authors: Hans Gerd Evertz, Gideon Lana, Mihai MarcuAbstract:We present a new type of Cluster Algorithm that strongly reduces critical slowing down in simulations of vertex models. Since the Clusters are closed paths of bonds, we call it the loop Algorithm. The basic steps in constructing a Cluster are the breakup and the freezing of vertices. We concentrate on the case of the F model, which is a subset of the six-vertex model exhibiting a Kosterlitz-Thouless transition. The loop Algorithm is also applicable to simulations of other vertex models and of one- and two-dimensional quantum spin systems