Random planar graphs and the London street network
A. P. Masucci, D. Smith, A. Crooks et al.
Data Analysis papers — page 104
physics.data-anBrowse archive
Methods for detection and characterization of signals in noisy data with the Hilbert-Huang Transform
Alexander Stroeer, John K. Cannizzo, Jordan B. Camp et al.Nonparametric estimation of the heterogeneity of a random medium using Compound Poisson Process modeling of wave multiple scattering
Nicolas Le Bihan, Ludovic MargerinGeneralised cascades
Silvio M. Duarte QueirosDetecting network communities by propagating labels under constraints
Michael J. Barber, John W. ClarkLimits of Declustering Methods for Disentangling Exogenous from Endogenous Events in Time Series with Foreshocks, Main shocks and Aftershocks
D. Sornette, S. UtkinJoint Bayesian endmember extraction and linear unmixing for hyperspectral imagery
Nicolas Dobigeon, Said Moussaoui, Martial Coulon et al.On the SIRs (Signal-to-Interference-Ratio) in Discrete-Time Autonomous Linear Networks
Zekeriya UykanStructure of shells in complex networks
Jia Shao, Sergey V. Buldyrev, Lidia A. Braunstein et al.The Dynamics of EEG Entropy
M. Ignaccolo, M. Latka, W. Jernajczyk et al.Waiting time dynamics of priority-queue networks
Byungjoon Min, K. -I. Goh, I. -M. KimBreakthrough in Interval Data Fitting II. From Ranges to Means and Standard Deviations
Marek W. GutowskiBreakthrough in Interval Data Fitting I. The Role of Hausdorff Distance
Marek W. GutowskiA data mining algorithm for automated characterisation of fluctuations in multichannel timeseries
D. G. Pretty, B. D. BlackwellUltimate "SIR" in Autonomous Linear Networks with Symmetric Weight Matrices, and Its Use to Stabilize the Network - A Hopfield-like network
Zekeriya UykanAnalysis of "SIR" ("Signal"-to-"Interference"-Ratio) in Discrete-Time Autonomous Linear Networks with Symmetric Weight Matrices
Zekeriya UykanThe relativity of theory
Nisheeth SrivastavaFrom Sigmoid Power Control Algorithm to Hopfield-like Neural Networks: "SIR"-Balancing Sigmoid-Based Networks- Part II: Discrete Time
Zekeriya UykanFrom Sigmoid Power Control Algorithm to Hopfield-like Neural Networks: "SIR" ("Signal"-to-"Interference"-Ratio)-Balancing Sigmoid-Based Networks- Part I: Continuous Time
Zekeriya UykanHow often does theory match experiment?
Anirban BanerjiProperties and application of the form A· exp(-(x-c)2/(a(x-c)+2b2)) for investigation of ultra high energy cascades
A. A. Kirillov, I. A. KirillovAbout the parabolic relation existing between the skewness and the kurtosis in time series of experimental data
F. Sattin, M. Agostini, R. Cavazzana et al.Dynamics of EEG Entropy: beyond signal plus noise
M. Ignaccolo, M. Latka, W. Jernajczyk et al.Bridge Bounding: A Local Approach for Efficient Community Discovery in Complex Networks
Symeon Papadopoulos, Andre Skusa, Athena Vakali et al.Detrended fluctuation analysis of power-law-correlated sequences with random noises
Shin-ichi Tadaki