Evaluating Data Assimilation AlgorithmsData assimilation leads naturally to a Bayesian formulation in which the posterior probability distribution of the system state, given the observations, plays a central conceptual role. The aim of…K. J. H. Law, A. M. Stuart·Mar 25, 2012SaveLearn
Imagiro: an implementation of Bayesian iterative unfolding for high energy physicsUnfolding of reconstructed event properties to identify the true features of collider events is a complementary method to the established practice of detector calibration, and is particularly…Benjamin Wynne·Mar 22, 2012SaveLearn
Semi-blind Sparse Image Reconstruction with Application to MRFMWe propose a solution to the image deconvolution problem where the convolution kernel or point spread function (PSF) is assumed to be only partially known. Small perturbations generated from the…Se Un Park, Nicolas Dobigeon, Alfred O. Hero·Mar 21, 2012SaveLearn
Analytical framework for recurrence-network analysis of time seriesRecurrence networks are a powerful nonlinear tool for time series analysis of complex dynamical systems. While there are already many successful applications ranging from medicine to…Jonathan F. Donges, Jobst Heitzig, Reik V. Donner et al.·Mar 21, 2012SaveLearn
Topology of Fracture NetworksWe propose a mapping from fracture systems consisting of intersecting fracture sheets in three dimensions to an abstract network consisting of nodes and links. This makes it possible to analyze…Christian André Andresen, Alex Hansen, Romain Le Goc et al.·Mar 19, 2012SaveLearn
Can a Lamb Reach a Haven Before Being Eaten by Diffusing Lions?We study the survival of a single diffusing lamb on the positive half line in the presence of N diffusing lions that all start at the same position L to the right of the lamb and a haven at x=0. If…Alan Gabel, Satya N. Majumdar, Nagendra K. Panduranga et al.·Mar 14, 2012SaveLearn
About the probability distribution of a quantity with given mean and varianceSupplement 1 to GUM (GUM-S1) recommends the use of maximum entropy principle (MaxEnt) in determining the probability distribution of a quantity having specified properties, e.g., specified central…Stefano Olivares, Matteo G. A. Paris·Mar 13, 2012SaveLearn
Analysis of stochastic time series in N dimensions in the presence of strong measurement noiseAn extension and generalization of a recently presented approach for the analysis of Langevin-type stochastic processes in the presence of strong measurement noise is presented. For a stochastic…B. Lehle·Mar 11, 2012SaveLearn
Noise correlation and decorrelation in arrays of bolometric detectorsBolometers are phonon mediated detectors used in particle physics experiments to search for rare processes, such as neutrinoless double beta decay and dark matter interactions. They feature an…C. Mancini-Terracciano, M. Vignati·Mar 8, 2012SaveLearn
RooStats for SearchesThe RooStats toolkit, which is distributed with the ROOT software package, provides a large collection of software tools that implement statistical methods commonly used by the High Energy Physics…Grégory Schott·Mar 7, 2012SaveLearn
Signal Recovery Using SplinesPractically, for all real measuring devices the result of a measurement is a convolution of an input signal with a hardware function of a unit ϕ. We call a spline to be ϕ-interpolating if the…Oleksandr Shumeyko, Ivan Devyatkin·Mar 1, 2012SaveLearn
Network Physiology reveals relations between network topology and physiological functionThe human organism is an integrated network where complex physiologic systems, each with its own regulatory mechanisms, continuously interact, and where failure of one system can trigger a breakdown…Amir Bashan, Ronny P. Bartsch, Jan W. Kantelhardt et al.·Mar 1, 2012SaveLearn
Perturbation of the Eigenvectors of the Graph Laplacian: Application to Image DenoisingThe original contributions of this paper are twofold: a new understanding of the influence of noise on the eigenvectors of the graph Laplacian of a set of image patches, and an algorithm to estimate…Francois G. Meyer, Xilin Shen·Feb 29, 2012SaveLearn
Spectral analysis and Allan variance calculation in the case of phase noiseIn this work, time series analysis techniques are used to analyze sequential, equispaced mass measurements of a Si density artifact, collected from an electromechanical transducer. Specifically,…Dimitra Georgakaki, Chris Mitsas, Hariton Polatoglou·Feb 29, 2012SaveLearn
Time series analysis of the response of measurement instrumentsIn this work the significance of treating a set of measurements as a time series is being explored. Time Series Analysis (TSA) techniques, part of the Exploratory Data Analysis (EDA) approach, can…Dimitra Georgakaki, Chris Mitsas, Hariton Polatoglou·Feb 29, 2012SaveLearn
Hyperspectral Unmixing Overview: Geometrical, Statistical, and Sparse Regression-Based ApproachesImaging spectrometers measure electromagnetic energy scattered in their instantaneous field view in hundreds or thousands of spectral channels with higher spectral resolution than multispectral…José M. Bioucas-Dias, Antonio Plaza, Nicolas Dobigeon et al.·Feb 28, 2012SaveLearn
Nonlinear Laplacian spectral analysis: Capturing intermittent and low-frequency spatiotemporal patterns in high-dimensional dataWe present a technique for spatiotemporal data analysis called nonlinear Laplacian spectral analysis (NLSA), which generalizes singular spectrum analysis (SSA) to take into account the nonlinear…Dimitrios Giannakis, Andrew J. Majda·Feb 28, 2012SaveLearn
Zero Mass Limit and Its Experimental TestJ. M. Sancho [Phys. Rev. E 84, 062102 (2011)] analyzed two stochastic interpretations on a recent experiment [Phys. Rev. Lett. 104, 170602 (2010)] of Brownian colloidal particles. The author asserted…Ruoshi Yuan, Ping Ao·Feb 26, 2012SaveLearn
Information flow in a network model and the law of diminishing marginal returnsWe analyze a simple dynamical network model which describes the limited capacity of nodes to process the input information. For a suitable choice of the parameters, the information flow pattern is…Daniele Marinazzo, Mario Pellicoro, Guorong Wu et al.·Feb 22, 2012SaveLearn
Data assimilation in the low noise regime with application to the KuroshioOn-line data assimilation techniques such as ensemble Kalman filters and particle filters lose accuracy dramatically when presented with an unlikely observation. Such an observation may be caused by…Eric Vanden-Eijnden, Jonathan Weare·Feb 22, 2012SaveLearn
Joining Forces of Bayesian and Frequentist Methodology: A Study for Inference in the Presence of Non-IdentifiabilityIncreasingly complex applications involve large datasets in combination with non-linear and high dimensional mathematical models. In this context, statistical inference is a challenging issue that…Andreas Raue, Clemens Kreutz, Fabian Joachim Theis et al.·Feb 21, 2012SaveLearn
Wind speed modeled as an indexed semi-Markov processThe increasing interest in renewable energy, particularly in wind, has given rise to the necessity of accurate models for the generation of good synthetic wind speed data. Markov chains are often…Guglielmo D'Amico, Filippo Petroni, Flavio Prattico·Feb 16, 2012SaveLearn
Scaling Laws in Human LanguageZipf's law on word frequency is observed in English, French, Spanish, Italian, and so on, yet it does not hold for Chinese, Japanese or Korean characters. A model for writing process is proposed…Linyuan Lu, Zi-Ke Zhang, Tao Zhou·Feb 14, 2012SaveLearn
Potential Theory for Directed NetworksUncovering factors underlying the network formation is a long-standing challenge for data mining and network analysis. In particular, the microscopic organizing principles of directed networks are…Qian-Ming Zhang, Linyuan Lü, Wen-Qiang Wang et al.·Feb 13, 2012SaveLearn
Forward Tracking in the ILD DetectorThe reconstruction software for ILD is currently subject to a major revision, aiming at improving its accuracy, speed, efficiency and maintainability in time for the upcoming DBD Report. This…Robin Glattauer, Rudolf Frühwirth, Jakob Lettenbichler et al.·Feb 13, 2012SaveLearn