Optimal adaptive multidimensional-time signal energy estimation on the background noiseWe construct an adaptive asymptotically optimal in the classical norm of the space L(2,Ω) of square integrable random variables the Energy estimation of a signal (function) observed in some points…Eugene Ostrovsky, Eugene Rogover, Leonid Sirota·Apr 26, 2010SaveLearn
Toy Model for Large Non-Symmetric Random MatricesNon-symmetric rectangular correlation matrices occur in many problems in economics. We test the method of extracting statistically meaningful correlations between input and output variables of large…Małgorzata Snarska·Apr 26, 2010SaveLearn
Markov Chain Analysis of Musical Dice GamesWe have studied entropy, redundancy, complexity, and first passage times to notes for 804 pieces of 29 composers. The successful understanding of tonal music calls for an experienced listener, as…J. R. Dawin, D. Volchenkov·Apr 23, 2010SaveLearn
Interdependent networks: Reducing the coupling strength leads to a change from a first to second order percolation transitionWe study a system composed from two interdependent networks A and B, where a fraction of the nodes in network A depends on the nodes of network B and a fraction of the nodes in network B depends on…Roni Parshani, Sergey V. Buldyrev, Shlomo Havlin·Apr 22, 2010SaveLearn
Hierarchical modularity in human brain functional networksThe idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life…D. Meunier, R. Lambiotte, A. Fornito et al.·Apr 19, 2010SaveLearn
Time and ensemble averaging in time series analysisIn many applications expectation values are calculated by partitioning a single experimental time series into an ensemble of data segments of equal length. Such single trajectory ensemble (STE) is a…Miroslaw Latka, Massimiliano Ignaccolo, Wojciech Jernajczyk et al.·Apr 13, 2010SaveLearn
Machine learning approach to inverse problem and unfolding procedureA procedure for unfolding the true distribution from experimental data is presented. Machine learning methods are applied for simultaneous identification of an apparatus function and solving of an…Nikolai Gagunashvili·Apr 12, 2010SaveLearn
Random matrix route to image denoisingWe make use of recent results from random matrix theory to identify a derived threshold, for isolating noise from image features. The procedure assumes the existence of a set of noisy images, where…Gaurab Basu, Kaushik Ray, Prasanta K. Panigrahi·Apr 8, 2010SaveLearn
The Anderson-Darling test of fit for the power law distribution from left censored samplesMaximum likelihood estimation and a test of fit based on the Anderson-Darling statistic is presented for the case of the power law distribution when the parameters are estimated from a left-censored…H. F. Coronel-Brizio, A. R. Hernandez-Montoya·Apr 3, 2010SaveLearn
Probability flux as a method for detecting scalingWe introduce a new method for detecting scaling in time series. The method uses the properties of the probability flux for stochastic self-affine processes and is called the probability flux analysis…M. Ignaccolo, P. Grigolini, B. J. West·Apr 2, 2010SaveLearn
Anomalous diffusion as a stochastic component in the dynamics of complex processesWe propose an interpolation expression using the difference moment (Kolmogorov transient structural function) of the second order as the average characteristic of displacements for identifying the…Serge F. Timashev, Yuriy S. Polyakov, Pavel I. Misurkin et al.·Apr 1, 2010SaveLearn
Entropy-based parametric estimation of spike train statisticsWe consider the evolution of a network of neurons, focusing on the asymptotic behavior of spikes dynamics instead of membrane potential dynamics. The spike response is not sought as a deterministic…J. C. Vasquez, B. Cessac, T. Viéville·Mar 16, 2010SaveLearn
Exact feature probabilities in images with occlusionTo understand the computations of our visual system, it is important to understand also the natural environment it evolved to interpret. Unfortunately, existing models of the visual environment are…Xaq Pitkow·Mar 15, 2010SaveLearn
Identifying phase synchronization clusters in spatially extended dynamical systemsWe investigate two recently proposed multivariate time series analysis techniques that aim at detecting phase synchronization clusters in spatially extended, nonstationary systems with regard to…Stephan Bialonski, Klaus Lehnertz·Mar 12, 2010SaveLearn
Entropy: The Markov Ordering ApproachThe focus of this article is on entropy and Markov processes. We study the properties of functionals which are invariant with respect to monotonic transformations and analyze two invariant…A. N. Gorban, P. A. Gorban, G. Judge·Mar 6, 2010SaveLearn
Zipf's law and log-normal distributions in measures of scientific output across fields and institutions: 40 years of Slovenia's research as an exampleSlovenia's Current Research Information System (SICRIS) currently hosts 86,443 publications with citation data from 8,359 researchers working on the whole plethora of social and natural sciences…Matjaz Perc·Mar 4, 2010SaveLearn
Similarity-Based Classification in Partially Labeled NetworksWe propose a similarity-based method, using the similarity between nodes, to address the problem of classification in partially labeled networks. The basic assumption is that two nodes are more…Qian-Ming Zhang, Ming-Sheng Shang, Linyuan Lu·Mar 3, 2010SaveLearn
Horizontal visibility graphs: exact results for random time seriesThe visibility algorithm has been recently introduced as a mapping between time series and complex networks. This procedure allows to apply methods of complex network theory for characterizing time…Bartolo Luque, Lucas Lacasa, Fernando Ballesteros et al.·Feb 24, 2010SaveLearn
Zipf's Law Leads to Heaps' Law: Analyzing Their Relation in Finite-Size SystemsBackground: Zipf's law and Heaps' law are observed in disparate complex systems. Of particular interests, these two laws often appear together. Many theoretical models and analyses are…Linyuan Lu, Zi-Ke Zhang, Tao Zhou·Feb 20, 2010SaveLearn
Effects of coarse-graining on the scaling behavior of long-range correlated and anti-correlated signalsWe investigate how various coarse-graining methods affect the scaling properties of long-range power-law correlated and anti-correlated signals, quantified by the detrended fluctuation analysis.…Yinlin Xu, Qianli D. Y. Ma, Daniel T. Schmitt et al.·Feb 19, 2010SaveLearn
Analysis of Birth weight using Singular Value DecompositionThe researchers have drawn much attention about the birth weight of newborn babies in the last three decades. The birth weight is one of the vital roles in the babys health. So many researchers such…D. Nagarajan, P. Sunitha, V. Nagarajan et al.·Feb 10, 2010SaveLearn
Detecting highly overlapping community structure by greedy clique expansionIn complex networks it is common for each node to belong to several communities, implying a highly overlapping community structure. Recent advances in benchmarking indicate that existing community…Conrad Lee, Fergal Reid, Aaron McDaid et al.·Feb 9, 2010SaveLearn
On the meaning of the h-indexThe h-index -- the value for which an individual has published at least h papers with at least h citations -- has become a popular metric to assess the citation impact of scientists. As already noted…S. Redner·Feb 4, 2010SaveLearn
Soccer: is scoring goals a predictable Poissonian process?The non-scientific event of a soccer match is analysed on a strictly scientific level. The analysis is based on the recently introduced concept of a team fitness (Eur. Phys. J. B 67, 445, 2009) and…Andreas Heuer, Christian Mueller, Oliver Rubner·Feb 3, 2010SaveLearn
Complex networks: new trends for the analysis of brain connectivityToday, the human brain can be studied as a whole. Electroencephalography, magnetoencephalography, or functional magnetic resonance imaging techniques provide functional connectivity patterns between…Mario Chavez, Miguel Valencia, Vito Latora et al.·Feb 3, 2010SaveLearn