Shrunken Locally Linear Embedding for Passive Microwave Retrieval of PrecipitationThis paper introduces a new Bayesian approach to the inverse problem of passive microwave rainfall retrieval. The proposed methodology relies on a regularization technique and makes use of two joint…Ardeshir Mohammad Ebtehaj, Rafael Luis Bras, Efi Foufoula-Georgiou·May 2, 2014SaveLearn
Finding metastable states in real-world time series with recurrence networksIn the framework of time series analysis with recurrence networks, we introduce a self-adaptive method that determines the elusive recurrence threshold and identifies metastable states in complex…Iliusi Vega, Christof Schütte, Tim O. F. Conrad·Apr 30, 2014SaveLearn
2-D Prony-Huang Transform: A New Tool for 2-D Spectral AnalysisThis work proposes an extension of the 1-D Hilbert Huang transform for the analysis of images. The proposed method consists in (i) adaptively decomposing an image into oscillating parts called…Jérémy Schmitt, Nelly Pustelnik, Pierre Borgnat et al.·Apr 30, 2014SaveLearn
Binary versus non-binary information in real time series: empirical results and maximum-entropy matrix modelsThe dynamics of complex systems, from financial markets to the brain, can be monitored in terms of multiple time series of activity of the constituent units, such as stocks or neurons respectively.…Assaf Almog, Diego Garlaschelli·Apr 29, 2014SaveLearn
Validating Predictions of Unobserved QuantitiesThe ultimate purpose of most computational models is to make predictions, commonly in support of some decision-making process (e.g., for design or operation of some system). The quantities that need…Todd A. Oliver, Gabriel Terejanu, Christopher S. Simmons et al.·Apr 29, 2014SaveLearn
Use of Correlation Matrix to Assess the Stirring Performance of a Reverberation Chamber: a Comparative StudyThe use of correlation matrices to evaluate the number of uncorrelated stirrer positions of reverberation chamber has widespread applications in electromagnetic compatibility. We present a…Gabriele Gradoni, Valter Mariani Primiani, Franco Moglie·Apr 25, 2014SaveLearn
Evolution of Force Networks in Dense Particulate MediaWe introduce novel sets of measures with the goal of describing dynamical properties of force networks in dense particulate systems. The presented approach is based on persistent homology and allows…Miroslav Kramar, Arnaud Goullet, Lou Kondic et al.·Apr 24, 2014SaveLearn
Fractional Laplace Transforms - A PerspectiveA form of the Laplace transform is reviewed as a paradigm for an entire class of fractional functional transforms. Various of its properties are discussed. Such transformations should be useful in…R. A. Treumann, W. Baumjohann·Apr 22, 2014SaveLearn
Zero-one-only process: a correlated random walk with a stochastic ratchetThe investigation of random walks is central to a variety of stochastic processes in physics, chemistry, and biology. To describe a transport phenomenon, we study a variant of the one-dimensional…Seung Ki Baek, Hawoong Jeong, Seung-Woo Son et al.·Apr 18, 2014SaveLearn
Evaluation of the training objectives with surface electromyographyIn this work the multifractal analysis of the kinesiological surface electromyographic signal is proposed. The goal was to investigate the level of neuromuscular activation during complex movements…Paulina Trybek, Michal Nowakowski, Lukasz Machura·Apr 16, 2014SaveLearn
Flood avalanches in a semiarid basin with a dense reservoir networkThis study investigates flood avalanches in a dense reservoir network in the semiarid north-eastern Brazil. The population living in this area strongly depends on the availability of the water from…Samuel J. Peter, J. C. de Araújo, N. A. M. Araújo et al.·Apr 16, 2014SaveLearn
Defining a Trend for a Time Series Which Makes Use of the Intrinsic Time-Scale DecompositionWe propose criteria that define a trend for time series with inherent multi-scale features. We call this trend the tendency of a time series. The tendency is defined empirically by a set of…Juan M. Restrepo, Shankar C. Venkataramani, Darin Comeau et al.·Apr 15, 2014SaveLearn
Negative probabilities and counter-factual reasoning in quantum cognitionIn this paper we discuss quantum-like decision-making experiments using negative probabilities. We do so by showing how the two-slit experiment, in the simplified version of the Mach-Zehnder…J. Acacio de Barros, Gary Oas·Apr 14, 2014SaveLearn
Hamiltonian formalism and path entropy maximizationMaximization of the path information entropy is a clear prescription for constructing models in non-equilibrium statistical mechanics. Here it is shown that, following this prescription under the…Sergio Davis, Diego González·Apr 11, 2014SaveLearn
Toward fits to scaling-like data, but with inflection points & generalized Lavalette functionExperimental and empirical data are often analyzed on log-log plots in order to find some scaling argument for the observed/examined phenomenon at hands, in particular for rank-size rule research,…Marcel Ausloos·Apr 11, 2014SaveLearn
Cycle flow based module detection in directed recurrence networksWe present a new cycle flow based method for finding fuzzy partitions of weighted directed networks coming from time series data. We show that this method overcomes essential problems of most…Ralf Banisch, Nataša Djurdjevac Conrad·Apr 10, 2014SaveLearn
Cluster analysis of weighted bipartite networks: a new copula-based approachIn this work we are interested in identifying clusters of "positional equivalent" actors, i.e. actors who play a similar role in a system. In particular, we analyze weighted bipartite…Alessandro Chessa, Irene Crimaldi, Massimo Riccaboni et al.·Apr 9, 2014SaveLearn
Reconstructing the intermittent dynamics of the torque in wind turbinesWe apply a framework introduced in the late nineties to analyze load measurements in off-shore wind energy converters (WEC). The framework is borrowed from statistical physics and properly adapted to…Pedro G. Lind, Matthias Wächter, Joachim Peinke·Apr 8, 2014SaveLearn
Modelling and analysis of turbulent datasets using ARMA processesWe introduce a novel way to extract information from turbulent datasets by applying an ARMA statistical analysis. Such analysis goes well beyond the analysis of the mean flow and of the fluctuations…Davide Faranda, Flavio Maria Emanuele Pons, Bérèngere Dubrulle et al.·Apr 2, 2014SaveLearn
Modeling and analysis of cyclic inhomogeneous Markov processes: a wind turbine case studyA method is proposed to reconstruct a cyclic time-inhomogeneous Markov pro- cess from measured data. First, a time-inhomogeneous Markov model is fit to the data, taken here from measurements on a…Teresa Scholz, Vitor V. Lopes, Pedro Lind et al.·Apr 1, 2014SaveLearn
Parameter estimation by fixed point of function of information processing intensityWe present a new method of estimating the dispersion of a distribution which is based on the surprising property of a function that measures information processing intensity. It turns out that this…Rober Jankowski, Marcin Makowski, Edward W. Piotrowski·Mar 31, 2014SaveLearn
Dynamical localization and eigenstate localization in trap modelsThe one-dimensional random trap model with a power-law distribution of mean sojourn times exhibits a phenomenon of dynamical localization in the case where diffusion is anomalous: The probability to…Franziska Flegel, Igor M. Sokolov·Mar 27, 2014SaveLearn
Confidence intervals with a priori parameter boundsWe review the methods of constructing confidence intervals that account for a priori information about one-sided constraints on the parameter being estimated. We show that the so-called method of…A. V. Lokhov, F. V. Tkachov·Mar 21, 2014SaveLearn
Parameter Estimation of Social Forces in Crowd Dynamics Models via a Probabilistic MethodFocusing on a specific crowd dynamics situation, including real life experiments and measurements, our paper targets a twofold aim: (1) we present a Bayesian probabilistic method to estimate the…Alessandro Corbetta, Adrian Muntean, Federico Toschi et al.·Mar 21, 2014SaveLearn
Exact detection of direct links in networks of interacting dynamical unitsThe inference of an underlying network topology from local observations of a complex system composed of interacting units is usually attempted by using statistical similarity measures, such as…Nicolás Rubido, Arturo C. Martí, Ezequiel Bianco-Martínez et al.·Mar 19, 2014SaveLearn