Skip to content

Data Analysis papers — page 136

physics.data-anBrowse archive

Probabilistic methods for data fusion
The main object of this paper is to show how we can use classical probabilistic methods such as Maximum Entropy (ME), maximum likelihood (ML) and/or Bayesian (BAYES) approaches to do microscopic and…
A. Mohammad-DjafariNov 14, 2001
Learn
Shape reconstruction in X-ray tomography from a small number of projections using deformable models
X-ray tomographic image reconstruction consists of determining an object function from its projections. In many applications such as non-destructive testing, we look for a fault region (air) in a…
A. Mohammad-Djafari, Ken SauerNov 14, 2001
Learn
Effect of nonstationarities on detrended fluctuation analysis
Detrended fluctuation analysis (DFA) is a scaling analysis method used to quantify long-range power-law correlations in signals. Many physical and biological signals are ``noisy'',…
Zhi Chen, Plamen Ch. Ivanov, Kun Hu et al.Nov 12, 2001
Learn
Entropy in Signal Processing (Entropie en Traitement du Signal)
Résumé: Le principal objet de cette communication est de faire une rétro perspective succincte de l'utilisation de l'entropie et du principe du maximum d'entropie dans le domaine du…
Ali Mohammad-DjafariNov 6, 2001
Learn
Model selection for inverse problems: Best choice of basis functions and model order selection
A complete solution for an inverse problem needs five main steps: choice of basis functions for discretization, determination of the order of the model, estimation of the hyperparameters, estimation…
A. Mohammad-DjafariNov 6, 2001
Learn
Bayesian source separation with mixture of Gaussians prior for sources and Gaussian prior for mixture coefficients
In this contribution, we present new algorithms to source separation for the case of noisy instantaneous linear mixture, within the Bayesian statistical framework. The source distribution prior is…
Hichem Snoussi, Ali Mohammad-DjafariNov 6, 2001
Learn
Penalized maximum likelihood for multivariate Gaussian mixture
In this paper, we first consider the parameter estimation of a multivariate random process distribution using multivariate Gaussian mixture law. The labels of the mixture are allowed to have a…
Hichem Snoussi, Ali Mohammad-DjafariNov 2, 2001
Learn
Bayesian inference for inverse problems
Traditionally, the MaxEnt workshops start by a tutorial day. This paper summarizes my talk during 2001'th workshop at John Hopkins University. The main idea in this talk is to show how the…
Ali Mohammad-DjafariOct 31, 2001
Learn
Reconstruction of dynamical equations for traffic flow
Traffic flow data collected by an induction loop detector on the highway close to Koeln-Nord are investigated with respect to their dynamics including the stochastic content. In particular we present…
S. Kriso, R. Friedrich, J. Peinke et al.Oct 29, 2001
Learn
Characterization of a Low Frequency Power Spectral Density f(-gamma) in a Threshold Model
his study investigates the modifications of the thermal spectrum, at low frequency, induced by an external damping on a system in heat contact with internal fluctuating impurities. Those impurities…
Erika D'AmbrosioOct 5, 2001
Learn
Stochastic models which separate fractal dimension and Hurst effect
Fractal behavior and long-range dependence have been observed in an astonishing number of physical systems. Either phenomenon has been modeled by self-similar random functions, thereby implying a…
Tilmann Gneiting, Martin SchlatherSep 13, 2001
Learn
On a quantitative method to analyse dynamical and measurement noise
This letter reports on a new method of analysing experimentally gained time series with respect to different types of noise involved, namely, we show that it is possible to differentiate between…
M. Siefert, J. Peinke, R. FriedrichAug 17, 2001
Learn
Quasi-optimal observables: Attaining the quality of maximal likelihood in parameter estimation when only a MC event generator is available
A new method of quasi-optimal observables allows one to approach the quality of data processing usually associated with the method of maximal likelihood within the simpler algorithmic context of…
F. V. TkachovAug 16, 2001
Learn
alphaPDE: A New Multivariate Technique for Parameter Estimation
We present alphaPDE, a new multivariate analysis technique for parameter estimation. The method is based on a direct construction of joint probability densities of known variables and the parameters…
B. Knuteson, H. Miettinen, L. HolmstromAug 1, 2001
Learn
Quantum Clustering
We propose a novel clustering method that is based on physical intuition derived from quantum mechanics. Starting with given data points, we construct a scale-space probability function. Viewing the…
David Horn, Assaf GottliebJul 25, 2001
Learn
Forecast and event control: On what is and what cannot be possible
Consequences of the basic and most evident consistency requirement-that measured events cannot happen and not happen at the same time-are shortly reviewed. Particular emphasis is given to event…
Karl SvozilJun 11, 2001
Learn
Statistics of Atmospheric Correlations
For a large class of quantum systems the statistical properties of their spectrum show remarkable agreement with random matrix predictions. Recent advances show that the scope of random matrix theory…
M. S. Santhanam, Prabir K. PatraMay 2, 2001
Learn
Strange Attractors in Multipath propagation: Detection and characterisation
Multipath propagation of radio waves in indoor/outdoor environments shows a highly irregular behavior as a function of time. Typical modeling of this phenomenon assumes the received signal is a…
C. Tannous, R. Davies, A. AngusApr 23, 2001
Learn
Complexity Through Nonextensivity
The problem of defining and studying complexity of a time series has interested people for years. In the context of dynamical systems, Grassberger has suggested that a slow approach of the entropy to…
William Bialek, Ilya Nemenman, Naftali TishbyMar 23, 2001
Learn
A Variational Formulation of Optimal Nonlinear Estimation
We propose a variational method to solve all three estimation problems for nonlinear stochastic dynamical systems: prediction, filtering, and smoothing. Our new approach is based upon a proper choice…
Gregory L. EyinkMar 18, 2001
Learn
A Good Measure for Bayesian Inference
The Gaussian theory of errors has been generalized to situations, where the Gaussian distribution and, hence, the Gaussian rules of error propagation are inadequate. The generalizations are based on…
Hanns L. HarneyMar 12, 2001
Learn
Effect of Trends on Detrended Fluctuation Analysis
Detrended fluctuation analysis (DFA) is a scaling analysis method used to estimate long-range power-law correlation exponents in noisy signals. Many noisy signals in real systems display trends, so…
Kun Hu, Plamen Ch. Ivanov, Zhi Chen et al.Mar 8, 2001
Learn
Deconvolution problems in x-ray absorption fine structure
A Bayesian method application to the deconvolution of EXAFS spectra is considered. It is shown that for purposes of EXAFS spectroscopy, from the infinitely large number of Bayesian solutions it is…
K. V. KlementevJan 30, 2001
Learn
Nonlinear limits to the information capacity of optical fiber communications
The exponential growth in the rate at which information can be communicated through an optical fiber is a key element in the so called information revolution. However, like all exponential growth…
Partha P. Mitra, Jason B. StarkNov 7, 2000
Learn
Capacity of multivariate channels with multiplicative noise: I.Random matrix techniques and large-N expansions for full transfer matrices
We study memoryless, discrete time, matrix channels with additive white Gaussian noise and input power constraints of the form Yi = Σj Hij Xj + Zi, where Yi ,Xj and Zi are…
Anirvan Mayukh Sengupta, Partha Pratim MitraOct 31, 2000
Learn
← PreviousPage 136Next →