Deep Graphs - a general framework to represent and analyze heterogeneous complex systems across scalesNetwork theory has proven to be a powerful tool in describing and analyzing systems by modelling the relations between their constituent objects. In recent years great progress has been made by…Dominik Traxl, Niklas Boers, Jürgen Kurths·Apr 4, 2016SaveLearn
A Noise-Robust Method with Smoothed 1/2 Regularization for Sparse Moving-Source MappingThe method described here performs blind deconvolution of the beamforming output in the frequency domain. To provide accurate blind deconvolution, sparsity priors are introduced with a smooth…Mai Quyen Pham, Benoit Oudompheng, Jérôme I. Mars et al.·Apr 1, 2016SaveLearn
Write error rate of spin-transfer-torque random access memory including micromagnetic effects using rare event enhancementSpin-transfer-torque random access memory (STT-RAM) is a promising candidate for the next-generation of random-access-memory due to improved scalability, read-write speeds and endurance. However, the…Urmimala Roy, Tanmoy Pramanik, Leonard F. Register et al.·Mar 28, 2016SaveLearn
A robust and passive method for geometric calibration of large arraysThis paper presents a complete strategy for the geometry estimation of large microphone arrays of arbitrary shape. Largeness is intended here in both number of microphones (hundreds) and size (few…Charles Vanwynsberghe, Pascal Challande, Jacques Marchal et al.·Mar 25, 2016SaveLearn
Statistical Uncertainty in Quantitative Neutron RadiographyWe demonstrate a novel procedure to calibrate neutron detection systems commonly used in standard neutron radiography. This calibration allows determining the uncertainties due to Poisson-like…Florian M. Piegsa, Anders P. Kaestner, Aldo Antognini et al.·Mar 22, 2016SaveLearn
Numerical Stability of Generalized EntropiesIn many applications, the probability density function is subject to experimental errors. In this work the continuos dependence of a class of generalized entropies on the experimental errors is…György Steinbrecher, Giorgio Sonnino·Mar 20, 2016SaveLearn
An Ensemble 4D Seismic History Matching Framework with Sparse Representation Based on Wavelet Multiresolution AnalysisIn this work we propose an ensemble 4D seismic history matching framework for reservoir characterization. Compared to similar existing frameworks in reservoir engineering community, the proposed one…Xiaodong Luo, Tuhin Bhakta, Morten Jakobsen et al.·Mar 15, 2016SaveLearn
Determination of the edge of criticality in echo state networks through Fisher information maximizationIt is a widely accepted fact that the computational capability of recurrent neural networks is maximized on the so-called "edge of criticality". Once the network operates in this…Lorenzo Livi, Filippo Maria Bianchi, Cesare Alippi·Mar 11, 2016SaveLearn
PySpike - A Python library for analyzing spike train synchronyUnderstanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing…Mario Mulansky, Thomas Kreuz·Mar 10, 2016SaveLearn
Measuring logic complexity can guide pattern discovery in empirical systemsWe explore a definition of complexity based on logic functions, which are widely used as compact descriptions of rules in diverse fields of contemporary science. Detailed numerical analysis shows…Marco Gherardi, Pietro Rotondo·Mar 7, 2016SaveLearn
The Langevin Approach: An R Package for Modeling Markov ProcessesWe describe an R package developed by the research group Turbulence, Wind energy and Stochastics (TWiSt) at the Carl von Ossietzky University of Oldenburg, which extracts the (stochastic) evolution…Philip Rinn, Pedro G. Lind, Matthias Wächter et al.·Mar 7, 2016SaveLearn
Reversible Markov chain estimation using convex-concave programmingWe present a convex-concave reformulation of the reversible Markov chain estimation problem and outline an efficient numerical scheme for the solution of the resulting problem based on a primal-dual…Benjamin Trendelkamp-Schroer, Hao Wu, Frank Noe·Mar 4, 2016SaveLearn
Modelling, controlling, predicting blackoutsThe electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the…Chengwei Wang, Celso Grebogi, Murilo S. Baptista·Mar 3, 2016SaveLearn
Variational estimation of the drift for stochastic differential equations from the empirical densityWe present a method for the nonparametric estimation of the drift function of certain types of stochastic differential equations from the empirical density. It is based on a variational formulation…Philipp Batz, Andreas Ruttor, Manfred Opper·Mar 3, 2016SaveLearn
Photographic dataset: random peppercornsThis is a photographic dataset collected for testing image processing algorithms. The idea is to have sets of different but statistically similar images. In this work the images show randomly…Teemu Helenius, Samuli Siltanen·Mar 3, 2016SaveLearn
Procedure to Approximately Estimate the Uncertainty of Material Ratio Parameters due to Inhomogeneity of Surface RoughnessRoughness parameters that characterize contacting surfaces with regard to friction and wear are commonly stated without uncertainties, or with an uncertainty only taking into account a very limited…Dorothee Hüser, Jonathan Hüser, Sebastian Rief et al.·Mar 2, 2016SaveLearn
Big Data Processing in Complex Hierarchical Network SystemsThis article covers the problem of processing of Big Data that describe process of complex networks and network systems operation. It also introduces the notion of hierarchical network systems…Olexandr Polishchuk, Dmytro Polishchuk, Maria Tyutyunnyk et al.·Mar 2, 2016SaveLearn
Superplot: a graphical interface for plotting and analysing MultiNest outputWe present an application, Superplot, for calculating and plotting statistical quantities relevant to parameter inference from a "chain" of samples drawn from a parameter space, produced by…Andrew Fowlie, Michael Hugh Bardsley·Mar 2, 2016SaveLearn
The Laura++ Dalitz plot fitterThe Laura++ software package is designed for performing fits of amplitude models to data from decays of spin-0 particles into final states containing three spin-0 particles - so-called Dalitz-plot…Thomas Latham·Mar 2, 2016SaveLearn
Eigenanalysis of morphological diversity in silicon random nanostructures formed via resist collapseThis paper demonstrates eigenanalysis to quantitatively reveal the diversity and capacity of identities offered by the morphological diversity in silicon nanostructures formed via random collapse of…Makoto Naruse, Morihisa Hoga, Yasuyuki Ohyagi et al.·Feb 26, 2016SaveLearn
The scaling of the minimum sum of edge lengths in uniformly random treesThe minimum linear arrangement problem on a network consists of finding the minimum sum of edge lengths that can be achieved when the vertices are arranged linearly. Although there are algorithms to…Juan Luis Esteban, Ramon Ferrer-i-Cancho, Carlos Gómez-Rodríguez·Feb 25, 2016SaveLearn
Computationally Efficient Calculations of Target Performance of the Normalized Matched Filter Detector for Hydrocoustic SignalsDetection of hydroacoustic transmissions is a key enabling technology in applications such as depth measurements, detection of objects, and undersea mapping. To cope with the long channel delay…Roee Diamant·Feb 24, 2016SaveLearn
Predicting dataset popularity for the CMS experimentThe CMS experiment at the LHC accelerator at CERN relies on its computing infrastructure to stay at the frontier of High Energy Physics, searching for new phenomena and making discoveries. Even…Valentin Kuznetsov, Ting Li, Luca Giommi et al.·Feb 23, 2016SaveLearn
Unfolding problem clarification and solution validationThe unfolding problem formulation for correcting experimental data distortions due to finite resolution and limited detector acceptance is discussed. A novel validation of the problem solution is…Nikolai Gagunashvili·Feb 18, 2016SaveLearn
Simulated Annealing Approach to the Temperature-Emissivity Separation Problem in Thermal Remote Sensing Part One: Mathematical BackgroundThe method of simulated annealing is adapted to the temperature-emissivity separation (TES) problem. A patch of surface at the bottom of the atmosphere is assumed to be a greybody emitter with…John A. Morgan·Feb 16, 2016SaveLearn