Algorithms for Identification of Nearly-Coincident Events in Calorimetric SensorsFor experiments with high arrival rates, reliable identification of nearly-coincident events can be crucial. For calorimetric measurements to directly measure the neutrino mass such as HOLMES,…B. Alpert, E. Ferri, D. Bennett et al.·Dec 5, 2015SaveLearn
Development of methods of the Fractal Dimension estimation for the ecological data analysisThis paper deals with an estimating of the Fractal Dimension of a hydrometeorology variables like an Air temperature or humidity at a different sites in a landscape (and will be further evaluated…Jakub Jura, Aleš Antonín Kuběna, Martina Mironovová·Dec 2, 2015SaveLearn
Sequential visibility-graph motifsVisibility algorithms transform time series into graphs and encode dynamical information in their topology, paving the way for graph-theoretical time series analysis as well as building a bridge…Jacopo Iacovacci, Lucas Lacasa·Dec 1, 2015SaveLearn
Non-judgemental Dynamic Fuel Cycle BenchmarkingThis paper presents a new fuel cycle benchmarking analysis methodology by coupling Gaussian process regression, a popular technique in Machine Learning, to dynamic time warping, a mechanism widely…Anthony Michael Scopatz·Nov 29, 2015SaveLearn
Automodel solutions for Lévy flight-based transport on a uniform backgroundA wide class of non-stationary superdiffusive transport on a uniform background with a power-law decay, at large distances, of the step-length probability distribution function (PDF) is shown to…A. B. Kukushkin, P. A. Sdvizhenskii·Nov 28, 2015SaveLearn
Non-Gaussian Parameter in k-Dimensional Euclidean SpaceWe generalize the non-Gaussian parameter, which is utilized to characterize the distinction of dynamics between realistic and Gaussian Brownian diffusions, in k-dimensional Euclidean space.Zihan Huang, Gaoming Wang, Zhao Yu·Nov 20, 2015SaveLearn
On non-Poissonian Voronoi tessellationsThe Voronoi tessellation is the partition of space for a given seeds pattern and the result of the partition depends completely on the type of given pattern "random", Poisson-Voronoi…M. Ferraro, L. Zaninetti·Nov 20, 2015SaveLearn
Hyperspectral Unmixing in Presence of Endmember Variability, Nonlinearity or Mismodelling EffectsThis paper presents three hyperspectral mixture models jointly with Bayesian algorithms for supervised hyperspectral unmixing. Based on the residual component analysis model, the proposed general…Abderrahim Halimi, Paul Honeine, Jose Bioucas-Dias·Nov 18, 2015SaveLearn
A framework for interpreting regularized state estimationFour-dimensional variational data assimilation (4D-Var) on a seasonal-to-interdecadal time scale under the existence of unstable modes can be viewed as an optimization problem of synchronized,…Nozomi Sugiura, Shuhei Masuda, Yosuke Fujii et al.·Nov 16, 2015SaveLearn
Negative Probabilities and ContextualityThere has been a growing interest, both in physics and psychology, in understanding contextuality in experimentally observed quantities. Different approaches have been proposed to deal with…J. Acacio de Barros, Janne Kujala, Gary Oas·Nov 9, 2015SaveLearn
Langevin power curve analysis for numerical WEC models with new insights on high frequency power performanceBased on the Langevin equation it has been proposed to obtain power curves for wind turbines from high frequency data of wind speed measurements u(t) and power output P (t). The two parts of the…Tanja A. Mücke, Matthias Wächter, Patrick Milan et al.·Nov 5, 2015SaveLearn
A Bayesian Consistent Dual Ensemble Kalman Filter for State-Parameter Estimation in Subsurface HydrologyEnsemble Kalman filtering (EnKF) is an efficient approach to addressing uncertainties in subsurface groundwater models. The EnKF sequentially integrates field data into simulation models to obtain a…Boujemaa Ait-El-Fquih, Mohamad El Gharamti, Ibrahim Hoteit·Nov 4, 2015SaveLearn
Big Data Is not just a New Type, but a New ParadigmThis paper is a first draft of the introduction to the special issue on volunteered geographic information published in Computers, Environment and Urban Systems (2015, 53, 1-122). In this short…Bin Jiang·Nov 4, 2015SaveLearn
Coarse-grained sensitivity for multiscale data assimilationWe show that the effective average action and its gradient are useful for solving multiscale data assimilation problems. We also present a procedure for numerically evaluating the gradient of the…Nozomi Sugiura·Oct 30, 2015SaveLearn
Real time Markov chains: Wind states in anemometric dataThe description of wind phenomena is frequently based on data obtained from anemometers, which usually report the wind speed and direction only in a horizontal plane. Such measurements are commonly…P. A. Sanchez, M. Robles, O. A. Jaramillo·Oct 27, 2015SaveLearn
Prospects of ratio and differential (δ) ratio based measurement-models: a case study for IRMS evaluationThe suitability of a mathematical-model Y = f(Xi) in serving a purpose whatsoever (should be preset by the function f specific input-to-output variation-rates, i.e.) can be judged beforehand. We…B. P. Datta·Oct 27, 2015SaveLearn
Parameter-free resolution of the superposition of stochastic signalsThis paper presents a direct method to obtain the deterministic and stochastic contribution of the sum of two independent sets of stochastic processes, one of which is composed by Ornstein-Uhlenbeck…Teresa Scholz, Frank Raischel, Vitor V. Lopes et al.·Oct 25, 2015SaveLearn
From empirical data to continuous Markov processes: a systematic approachWe present an approach for testing for the existence of continuous generators of discrete stochastic transition matrices. Typically, the known approaches to ascertain the existence of continuous…Pedro Lencastre, Frank Raischel, Tim Rogers et al.·Oct 25, 2015SaveLearn
Data-driven detrending of nonstationary fractal time series with echo state networksIn this paper, we propose a novel data-driven approach for removing trends (detrending) from nonstationary, fractal and multifractal time series. We consider real-valued time series relative to…Enrico Maiorino, Filippo Maria Bianchi, Lorenzo Livi et al.·Oct 24, 2015SaveLearn
Characterization of river flow fluctuations via horizontal visibility graphsWe report on a large-scale characterization of river discharges by employing the network framework of the horizontal visibility graph. By mapping daily time series from 141 different stations of 53…A. C. Braga, L. G. A. Alves, L. S. Costa et al.·Oct 23, 2015SaveLearn
A note on the best invariant estimation of continuous probability distributions under mean square lossWe consider the nonparametric estimation problem of continuous probability distribution functions. For the integrated mean square error we provide the statistic corresponding to the best invariant…Thomas Schürmann·Oct 21, 2015SaveLearn
Online Unmixing of Multitemporal Hyperspectral Images accounting for Spectral VariabilityHyperspectral unmixing is aimed at identifying the reference spectral signatures composing an hyperspectral image and their relative abundance fractions in each pixel. In practice, the identified…Pierre-Antoine Thouvenin, Nicolas Dobigeon, Jean-Yves Tourneret·Oct 20, 2015SaveLearn
Structure of force networks in tapped particulate systems of disks and pentagons (Part 2): Persistence analysisIn the companion paper~paper1, we use classical measures based on force probability density functions (PDFs), as well as Betti numbers (quantifying the number of components, related to force…L. Kondic, M. Kramar, L. A. Pangolin et al.·Oct 14, 2015SaveLearn
Coupled uncertainty provided by a multifractal random walkerThe aim here is to study the concept of pairing multifractality between time series possessing non-Gaussian distributions. The increasing number of rare events creates "criticality". We show…Z. Koohi Lai, S. Vasheghani Farahani, S. M. S. Movahed et al.·Oct 11, 2015SaveLearn
Data-driven prediction and prevention of extreme events in a spatially extended excitable systemExtreme events occur in many spatially extended dynamical systems, often devastatingly affecting human life which makes their reliable prediction and efficient prevention highly desirable. We study…Stephan Bialonski, Gerrit Ansmann, Holger Kantz·Oct 8, 2015SaveLearn