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Source Separation Using Higher Order Moments
 in Proc. ICASSP
, 1989
"... This communication presents a simple algebraic method for the extraction of independent components in multidimensional data. Since statistical independence is a much stronger property than uncorrelation, it is possible, using higherorder moments, to identify source signatures in array data without ..."
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Cited by 121 (7 self)
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This communication presents a simple algebraic method for the extraction of independent components in multidimensional data. Since statistical independence is a much stronger property than uncorrelation, it is possible, using higherorder moments, to identify source signatures in array data without
Invertibility of HigherOrder Moment Matrices
, 1995
"... Signal processing algorithms based on Volterra filter structures often require that a matrix composed of higherorder moments of the underlying process be invertible. Previously, this problem has been studied for uncorrelated random variables. This paper establishes conditions under which a wide cla ..."
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Signal processing algorithms based on Volterra filter structures often require that a matrix composed of higherorder moments of the underlying process be invertible. Previously, this problem has been studied for uncorrelated random variables. This paper establishes conditions under which a wide
New ThirdOrder Moments for the CBL
"... Turbulent convectionis an inherently nonlocal phenomenonand a primary condition for a successfultreatment of the CBL (convective boundary layer) is a reliable model of nonlocality. In the dynamic equationsgoverningthe convectiveflux, the turbulent kinetic energy, etc., nonlocality is representedb ..."
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locality is representedby the thirdorder moments, TOMs. Since the simplestform, the socalled downgradient approximation (DGA), severelyunderestimates the TOMs (up to an order of magnitude), a more physical model is needed.In 1994,an analytical model was presentedwhich was derived directly,rom the dynamical equations
Global Optimization with Polynomials and the Problem of Moments
 SIAM Journal on Optimization
, 2001
"... We consider the problem of finding the unconstrained global minimum of a realvalued polynomial p(x) : R R, as well as the global minimum of p(x), in a compact set K defined by polynomial inequalities. It is shown that this problem reduces to solving an (often finite) sequence of convex linear mat ..."
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Cited by 569 (47 self)
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matrix inequality (LMI) problems. A notion of KarushKuhnTucker polynomials is introduced in a global optimality condition. Some illustrative examples are provided. Key words. global optimization, theory of moments and positive polynomials, semidefinite programming AMS subject classifications. 90C22
The space complexity of approximating the frequency moments
 JOURNAL OF COMPUTER AND SYSTEM SCIENCES
, 1996
"... The frequency moments of a sequence containing mi elements of type i, for 1 ≤ i ≤ n, are the numbers Fk = �n i=1 mki. We consider the space complexity of randomized algorithms that approximate the numbers Fk, when the elements of the sequence are given one by one and cannot be stored. Surprisingly, ..."
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Cited by 855 (12 self)
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The frequency moments of a sequence containing mi elements of type i, for 1 ≤ i ≤ n, are the numbers Fk = �n i=1 mki. We consider the space complexity of randomized algorithms that approximate the numbers Fk, when the elements of the sequence are given one by one and cannot be stored. Surprisingly
IMAGE RECONSTRUCTION BY MINIMIZING SECONDORDER MOMENT
"... Statistical methods have received much attention in image reconstruction, especially when the projection data are not sufficient in number, since they usually give more reliable results in such a case than other methods. In this paper, we propose a new statistical method which minimizes the second ..."
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moment of an object that indicates the variance and randomness in a statistical structure. By minimizing the secondorder moment, the resulting image reflects the statistical structure imposed by the available information and is biased toward a flat gray structure in the absence of information
Evaluating the Accuracy of SamplingBased Approaches to the Calculation of Posterior Moments
 IN BAYESIAN STATISTICS
, 1992
"... Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical accurac ..."
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Cited by 583 (14 self)
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Data augmentation and Gibbs sampling are two closely related, samplingbased approaches to the calculation of posterior moments. The fact that each produces a sample whose constituents are neither independent nor identically distributed complicates the assessment of convergence and numerical
FourthOrder Moments of Nonnegative Measures on S 2 and Applications
"... This paper is mainly devoted to a study of the fifteendimensional setof all fourthorder moments of a nonnegative Radon (Borel regular) measure on S 2. We seek a complete characterization f the set, a closed cone, with the help of the Hilbert decomposition theorem for nonnegative polynomials of deg ..."
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This paper is mainly devoted to a study of the fifteendimensional setof all fourthorder moments of a nonnegative Radon (Borel regular) measure on S 2. We seek a complete characterization f the set, a closed cone, with the help of the Hilbert decomposition theorem for nonnegative polynomials
Nonparametric Estimation of HigherOrder Moments of Technical Efficiency
, 2006
"... In this paper nonparametric techniques are used to estimate higherorder moments of technical efficiency. The procedures given in this paper allow the moments to be estimated with relative ease, while at the same not requiring restrictive assumptions on the distribution of inefficiency. The results ..."
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In this paper nonparametric techniques are used to estimate higherorder moments of technical efficiency. The procedures given in this paper allow the moments to be estimated with relative ease, while at the same not requiring restrictive assumptions on the distribution of inefficiency. The results
Results 1  10
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1,013,453