Bstj 48: 10. December 1969: an Extended correlation function of Two Random Variables Applied to Mobile Radio Transmission. (Lee, W.C.Y.) by published by
Bstj 48: 10. December 1969: an Extended correlation function of Two Random Variables Applied to Mobile Radio Transmission. (Lee, W.C.Y.) by published by
Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion...
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Blind separation of source signals usually relies either on the condition of statistically independence or involving their higher-order cumulants. The model of two channels signal separation is considered. A criterion based on correlation functions is proposed. It is proved that the signals can be separated, using only the condition of noncorrelation. An algorithm is derived, which only involves the solution to quadric nonlinear equations.
Recently, simple dynamical systems such as the 1-d maps on the interval, gained significant attention in the context of statistical physics and complex systems. The decay of correlations in these systems, can be chara...
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Recently, simple dynamical systems such as the 1-d maps on the interval, gained significant attention in the context of statistical physics and complex systems. The decay of correlations in these systems, can be characterized and measured by correlation functions. In the context of symbolic dynamics of the nonchaotic multifractal attractors (i.e. Feigenbaum attractors), one observable, the symbol-to-symbol correlation function, for the generating partition of the logistic map, is rigorously introduced and checked by numerical experiments. Thanks to the Metropolis-Stein-Stein (MSS) algorithm, this observable can be calculated analytically, giving predictions in absolute accordance with numerical computations. The deep, algorithmic structure of the observable is revealed clearly reflecting the complexity of the multifractal attractor.
The correlation function-based methods have been widely in the operational modal analysis of engineering structures. However, the understanding of the advantages and disadvantages of these methods for modal estimation...
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The correlation function-based methods have been widely in the operational modal analysis of engineering structures. However, the understanding of the advantages and disadvantages of these methods for modal estimation remains limited, which may result in inappropriate settings for key parameters adopted in these methods, thereby introducing errors in modal identification. Besides, the non-stationary features of the responses of highrise buildings under severe wind conditions are a critical factor affecting the accuracy of modal estimates. To address these issues, the performances of several widely used correlation function-based methods are investigated via numerical simulation study of a frame structure. Then, two time-frequency domain methods with obvious advantages are selected and employed to analyze the dynamic responses of a 600 m high supertall building to determine the key parameters adopted in these techniques, and further evaluate the dynamic properties of the skyscraper during two super typhoons. Based on the reliable modal estimates, the time-varying features and amplitude dependency of modal properties as well as the natural frequency-dependent feature in damping ratios are presented and discussed. This paper aims to present effective tools for modal estimation through assessing the performances of the correlation function-based methods and determining the key settings in these methods as well as reveal the dynamic characteristics of high-rise buildings under severe typhoon conditions.
Atrial fibrillation (AF) is a common cardiac arrhythmia in clinic. The traditional AF detection using visual inspection by trained physicians is an inefficient and burdensome task. In this paper, we introduce a novel ...
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Atrial fibrillation (AF) is a common cardiac arrhythmia in clinic. The traditional AF detection using visual inspection by trained physicians is an inefficient and burdensome task. In this paper, we introduce a novel method for the automated AF detection using two-lead electrocardiogram (ECG) signals. We use the wavelet packet transform (WPT) and the correlation function of random process theory to devise an efficient feature extraction strategy for physiological signal analysis, and construct the corresponding histogram. Then, multivariate statistical features based on the correlation among wavelet coefficient series are extracted from the corresponding histogram as the feature set, which is the input to artificial neural network (ANN) classifier for the detection. Moreover, various statistical analyses are performed and some parameter tuning strategies are formulated by fitting the receiver operating characteristic (ROC) curve to ensure the reliability and robustness of the work. To evaluate the classification performance of the algorithm, 10-fold cross-validation is implemented on the MIT-BIH AF database. Compared with some state-of-the-art algorithms, the numerical results prove that our proposed strategy yields superior classification performance. To the best of our knowledge, this is also the first application of random process theory for AF detection, providing great potential in medical diagnosis. (C) 2019 Elsevier Ltd. All rights reserved.
Algorithms of the parametric estimation of the correlation function of the polarized thermal light with the Lorentz, Gaussian and rectangular spectra, based on single-and first-event detection in the counting interval...
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Algorithms of the parametric estimation of the correlation function of the polarized thermal light with the Lorentz, Gaussian and rectangular spectra, based on single-and first-event detection in the counting interval, are explored by means of simulation. The dependence of the statistical identifiability of the particular correlation function on the number of collected counts is demonstrated.
We evaluate the correlation function of a radar signal scattered by inhomogeneities of turbulent medium and received by a radar station at the output of the matched filter. For the turbulent medium, we employ the mode...
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We evaluate the correlation function of a radar signal scattered by inhomogeneities of turbulent medium and received by a radar station at the output of the matched filter. For the turbulent medium, we employ the model of wandering inhomogeneities, which is a generalization of the ‘frozen’ turbulence. The concepts of strong and weak wanderings are introduced. The case of bistatic radar station is considered. For a monostatic radar station, simple asymptotic formulas are obtained. It is shown that, in the short-wavelength limit, wanderings are almost always strong, and in the long-wavelength limit, the weak wandering limit takes place mainly in the long-wavelength approximation.
This work introduces a new, compactly supported correlation function that can be inhomogeneous over Euclidean three-space, anisotropic when restricted to the sphere, and compactly supported on regions other than spher...
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This work introduces a new, compactly supported correlation function that can be inhomogeneous over Euclidean three-space, anisotropic when restricted to the sphere, and compactly supported on regions other than spheres of fixed radius. This function, which we call the Generalized Gaspari-Cohn (GenGC) correlation function, is a generalization of the compactly supported, piecewise rational approximation to a Gaussian introduced by Gaspari and Cohn in 1999 and its subsequent extension by Gaspari et al in 2006. The GenGC correlation function is a parametric correlation function that allows two parameters a$$ a $$ and c$$ c $$ to vary, as functions, over space, whereas the earlier formulations either keep both a$$ a $$ and c$$ c $$ fixed or only allow a$$ a $$ to vary. Like these earlier formulations, GenGC is a sixth-order piecewise rational function (fifth-order near the origin), while the coefficients now depend explicitly on the values of both a$$ a $$ and c$$ c $$ at each pair of points being correlated. We show that, by allowing both a$$ a $$ and c$$ c $$ to vary, the correlation length of GenGC also varies over space and introduces inhomogeneous and anisotropic features that may be useful in data assimilation applications. Covariances produced using GenGC are computationally tractable due to their compact support and have the added flexibility of generating compact support regions that adapt to the input c$$ c $$ field. These features can be useful for covariance modeling and covariance tapering applications in data assimilation. We derive the GenGC correlation function using convolutions, discuss continuity properties relating to a$$ a $$ and c$$ c $$ and its correlation length, and provide one- and two-dimensional examples that highlight its anisotropy and variable regions of compact support.
作者：
Najafi, MohsenAEOI
Nucl Sci & Technol Res Inst Mat & Nucl Fuel Res Sch Tehran Iran
In this paper, we calculate Joule-Thomson, the enthalpy changes relative to the pressure and deviation functions at low pressure for refrigerant fluids in order to evaluate the performance of their correlation functio...
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In this paper, we calculate Joule-Thomson, the enthalpy changes relative to the pressure and deviation functions at low pressure for refrigerant fluids in order to evaluate the performance of their correlation function. The studied refrigerants are R11, R123, R124, R134a, R143a, R152a, R141b, R142b, R227ea, and R236ea. The studied corresponding state principle is the one suggested by Meng et al. In addition, to compare with the data obtained by others, Boyle temperature, Boyle volume, and maximum inversion temperature were also calculated using the correlation. The obtained results show that the correlation equation presented has a good ability to predict the thermophysical properties of materials and their deviation from the ideal state over a wide range of temperatures.
Resonant characteristics in double-barrier tunneling structures are analyzed taking the effects of phase breaking into consideration. The correlation function is used to express the degree of phase coherence during th...
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Resonant characteristics in double-barrier tunneling structures are analyzed taking the effects of phase breaking into consideration. The correlation function is used to express the degree of phase coherence during the multiple reflection, in the Fabry-Perot resonator. This treatment promises preservation of the probability current and describes broadening of the resonant peak due to phase breaking.
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