Practical Introduction to Clustering DataData clustering is an approach to seek for structure in sets of complex data, i.e., sets of "objects". The main objective is to identify groups of objects which are similar to each other,…Alexander K. Hartmann·Feb 16, 2016SaveLearn
Prediction of Dynamical Systems by Symbolic RegressionWe study the modeling and prediction of dynamical systems based on conventional models derived from measurements. Such algorithms are highly desirable in situations where the underlying dynamics are…Markus Quade, Markus Abel, Kamran Shafi et al.·Feb 15, 2016SaveLearn
Non-spectral modes and how to find them in the Ornstein-Uhlenbeck process with white μ-stable noiseWe consider the Ornstein-Uhlenbeck process with a broad initial probability distribution (Levy distribution), which exhibits so-called non-spectral modes. The relaxation of such modes differs from…F. Thiel, I. M. Sokolov, E. B. Postnikov·Feb 13, 2016SaveLearn
Identifying Excessively Rounded or Truncated DataAll data are digitized, and hence are essentially integers rather than true real numbers. Ordinarily this causes no difficulties since the truncation or rounding usually occurs below the noise level.…Kevin H. Knuth, J. Patrick Castle, Kevin R. Wheeler·Feb 13, 2016SaveLearn
Modeling of critical experiments and its impact on integral covariance matrices and correlation coefficientsIn this manuscript we study the modeling of experimental data and its impact on the resulting integral experimental covariance and correlation matrices. By investigating a set of three low enriched…Elisabeth Peters, Fabian Sommer, Maik Stuke·Feb 12, 2016SaveLearn
On methods for correcting for the look-elsewhere effect in searches for new physicsThe search for new significant peaks over a energy spectrum often involves a statistical multiple hypothesis testing problem. Separate tests of hypothesis are conducted at different locations…Sara Algeri, David A. van Dyk, Jan Conrad et al.·Feb 11, 2016SaveLearn
On the potential of multivariate techniques for the determination of multidimensional efficienciesDifferential measurements of particle collisions or decays can provide stringent constraints on physics beyond the Standard Model of particle physics. In particular, the distributions of the…Benoit Viaud·Feb 11, 2016SaveLearn
Displacement Data AssimilationWe show that modifying a Bayesian data assimilation scheme by incorporating kinematically-consistent displacement corrections produces a scheme that is demonstrably better at estimating partially…W. Steven Rosenthal, Shankar C. Venkataramani, Arthur J. Mariano et al.·Feb 6, 2016SaveLearn
Particle identification in ALICE: a Bayesian approachWe present a Bayesian approach to particle identification (PID) within the ALICE experiment. The aim is to more effectively combine the particle identification capabilities of its various detectors.…ALICE Collaboration·Feb 3, 2016SaveLearn
Expansion-maximization-compression algorithm with spherical harmonics for single particle imaging with X-ray lasersIn 3D single particle imaging with X-ray free-electron lasers, particle orientation is not recorded during measurement but is instead recovered as a necessary step in the reconstruction of a 3D image…Julien Flamant, Nicolas Le Bihan, Andrew V. Martin et al.·Feb 3, 2016SaveLearn
Detrending Moving Average Algorithm: Frequency Response and Scaling PerformancesThe Detrending Moving Average (DMA) algorithm has been widely used in its several variants for characterizing long-range correlations of random signals and sets (one-dimensional sequences or…Anna Carbone, Ken Kiyono·Feb 3, 2016SaveLearn
Development of an Ideal Observer that Incorporates Nuisance Parameters and Processes List-Mode DataObserver models were developed to process data in list-mode format in order to perform binary discrimination tasks for use in an arms-control-treaty context. Data used in this study was generated…Christopher J. MacGahan, Matthew A. Kupinski, Nathan R. Hilton et al.·Feb 2, 2016SaveLearn
SHARP: a distributed, GPU-based ptychographic solverEver brighter light sources, fast parallel detectors, and advances in phase retrieval methods, have made ptychography a practical and popular imaging technique. Compared to previous techniques,…Stefano Marchesini, Hari Krishnan, Benedikt J. Daurer et al.·Jan 30, 2016SaveLearn
Tempered Fractional Feynman-Kac EquationFunctionals of Brownian/non-Brownian motions have diverse applications and attracted a lot of interest of scientists. This paper focuses on deriving the forward and backward fractional Feynman-Kac…Xiaochao Wu, Weihua Deng, Eli Barkai·Jan 30, 2016SaveLearn
Dynamic system classifierStochastic differential equations describe well many physical, biological and sociological systems, despite the simplification often made in their derivation. Here the usage of simple stochastic…Daniel Pumpe, Maksim Greiner, Ewald Müller et al.·Jan 28, 2016SaveLearn
Blind fluorescence structured illumination microscopy: A new reconstruction strategyIn this communication, a fast reconstruction algorithm is proposed for fluorescence blind structured illumination microscopy (SIM) under the sample positivity constraint. This new algorithm…S. Labouesse, M. Allain, J. Idier et al.·Jan 28, 2016SaveLearn
On the use of financial analysis tools for the study of Dst time series in the frame of complex systemsTechnical analysis is considered the oldest, currently omnipresent, method for financial markets analysis, which uses past prices aiming at the possible short-term forecast of future prices. In the…Stelios M. Potirakis, Pavlos I. Zitis, Georgios Balasis et al.·Jan 27, 2016SaveLearn
Investigating echo state networks dynamics by means of recurrence analysisIn this paper, we elaborate over the well-known interpretability issue in echo state networks. The idea is to investigate the dynamics of reservoir neurons with time-series analysis techniques taken…Filippo Maria Bianchi, Lorenzo Livi, Cesare Alippi·Jan 26, 2016SaveLearn
On causality of extreme eventsMultiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we…Massimiliano Zanin·Jan 26, 2016SaveLearn
Model uncertainty and reference value of the Planck constantStatistical parametric models are proposed to explain the values of the Planck constant obtained by comparing electrical and mechanical powers and by counting atoms in Si 28 enriched crystals. They…Giovanni Mana·Jan 21, 2016SaveLearn
Self-similar continuous cascades supported by random Cantor sets. Application to rainfall dataWe introduce a variant of continuous random cascade models that extends former constructions introduced by Barral-Mandelbrot and Bacry-Muzy in the sense that they can be supported by sets of…J. F. Muzy, R. Baïle·Jan 14, 2016SaveLearn
Multi-model Cross Pollination in TimePredictive skill of complex models is often not uniform in model-state space; in weather forecasting models, for example, the skill of the model can be greater in populated regions of interest than…Hailiang Du, Leonard A. Smith·Jan 7, 2016SaveLearn
Nonparametric Maximum Entropy Estimation on Information DiagramsMaximum entropy estimation is of broad interest for inferring properties of systems across many different disciplines. In this work, we significantly extend a technique we previously introduced for…Elliot A. Martin, Jaroslav Hlinka, Alexander Meinke et al.·Jan 3, 2016SaveLearn
Amplitude estimation of a sine function based on confidence intervals and Bayes' theoremThis paper discusses the amplitude estimation using data originating from a sine-like function as probability density function. If a simple least squares fit is used, a significant bias is observed…Dennis Eversmann, Jörg Pretz, Marcel Rosenthal·Dec 29, 2015SaveLearn
Complex Network Approach to Fractional Time SeriesIn order to extract correlation information inherited in stochastic time series, the visibility graph algorithm has been recently proposed, by which a time series can be mapped onto a complex…Pouya Manshour·Dec 27, 2015SaveLearn