The Experts below are selected from a list of 258 Experts worldwide ranked by ideXlab platform
Huijie Yang - One of the best experts on this subject based on the ideXlab platform.
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Scaling invariance embedded in very short time series: A Factorial Moment based diffusion entropy approach
Chinese Journal of Physics, 2017Co-Authors: Yue Yang, Lu Qiu, Tianguang Yang, Liying Hou, Huijie YangAbstract:Abstract How to evaluate scaling behaviors in very short time series is still an open problem, in which the mechanism-dependence and the bias of estimation of a statistical quantity become critical. We propose a new method called Factorial Moment based diffusion entropy (FMDE). A theoretical derivation and extensive calculations show that it can give us a high-confident and unbiased evaluation of scaling exponent from a time series with a length of ∼ 102. It provides a reliable method to monitor evolutionary behaviors of complex systems. As an illustration, it is used to monitor the fractal gait rhythm for a volunteer in six stride trials. We find rich patterns in its physiological state.
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Multifractals embedded in short time series: An unbiased estimation of probability Moment.
Physical Review E, 2016Co-Authors: Lu Qiu, Tianguang Yang, Yanhua Yin, Huijie YangAbstract:An exact estimation of probability Moments is the base for several essential concepts, such as the multifractals, the Tsallis entropy, and the transfer entropy. By means of approximation theory we propose a new method called Factorial-Moment-based estimation of probability Moments. Theoretical prediction and computational results show that it can provide us an unbiased estimation of the probability Moments of continuous order. Calculations on probability redistribution model verify that it can extract exactly multifractal behaviors from several hundred recordings. Its powerfulness in monitoring evolution of scaling behaviors is exemplified by two empirical cases, i.e., the gait time series for fast, normal, and slow trials of a healthy volunteer, and the closing price series for Shanghai stock market. By using short time series with several hundred lengths, a comparison with the well-established tools displays significant advantages of its performance over the other methods. The Factorial-Moment-based estimation can evaluate correctly the scaling behaviors in a scale range about three generations wider than the multifractal detrended fluctuation analysis and the basic estimation. The estimation of partition function given by the wavelet transform modulus maxima has unacceptable fluctuations. Besides the scaling invariance focused in the present paper, the proposed Factorial Moment of continuous order can find its various uses, such as finding nonextensive behaviors of a complex system and reconstructing the causality relationship network between elements of a complex system.
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Scaling invariance in spectra of complex networks: a diffusion Factorial Moment approach.
Physical review. E Statistical nonlinear and soft matter physics, 2005Co-Authors: Fangcui Zhao, Huijie Yang, Binghong WangAbstract:A new method called diffusion Factorial Moment is used to obtain scaling features embedded in the spectra of complex networks. For an Erdos-Renyi network with connecting probability p(ER) < 1/N, the scaling parameter is delta = 0.51, while for p(ER) > or = 1/N the scaling parameter deviates from it significantly. For WS small-world networks, in the special region p(r) element of [0.05,0.2], typical scale invariance is found. For growing random networks, in the range of theta element of [0.33,049], we have delta = 0.6 +.- 0.1. And the value of delta oscillates around delta = 0.6 abruptly. In the range of delta element of [0.54,1], we have basically element of > 0.7. Scale invariance is one of the common features of the three kinds of networks, which can be employed as a global measurement of complex networks in a unified way.
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Scaling invariance in spectra of complex networks: a diffusion Factorial Moment approach.
Physical Review E, 2005Co-Authors: Fangcui Zhao, Huijie Yang, Binghong WangAbstract:A new method called diffusion Factorial Moment is used to obtain scaling features embedded in the spectra of complex networks. For an Erdos-Renyi network with connecting probability ${p}_{\mathit{ER}}l1∕N$, the scaling parameter is $\ensuremath{\delta}=0.51$, while for ${p}_{\mathit{ER}}\ensuremath{\geqslant}1∕N$ the scaling parameter deviates from it significantly. For WS small-world networks, in the special region ${p}_{r}∊[0.05,0.2]$, typical scale invariance is found. For growing random networks, in the range of $\ensuremath{\theta}∊[0.33,049]$, we have $\ensuremath{\delta}=0.6\ifmmode\pm\else\textpm\fi{}0.1$. And the value of $\ensuremath{\delta}$ oscillates around $\ensuremath{\delta}=0.6$ abruptly. In the range of $\ensuremath{\theta}∊[0.54,1]$, we have basically $\ensuremath{\delta}g0.7$. Scale invariance is one of the common features of the three kinds of networks, which can be employed as a global measurement of complex networks in a unified way.
Bartlomiej Blaszczyszyn - One of the best experts on this subject based on the ideXlab platform.
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Studying the SINR Process of the Typical User in Poisson Networks Using Its Factorial Moment Measures
IEEE Transactions on Information Theory, 2015Co-Authors: Bartlomiej Blaszczyszyn, Holger Paul KeelerAbstract:Based on a stationary Poisson point process, a wireless network model with random propagation effects (shadowing and/or fading) is considered in order to examine the process formed by the signal-to-interference-plus-noise ratio (SINR) values experienced by a typical user with respect to all base stations in the down-link channel. This SINR process is completely characterized by deriving its Factorial Moment measures, which involve numerically tractable, explicit integral expressions. This novel framework naturally leads to expressions for the k-coverage probability, including the case of random SINR threshold values considered in multi-tier network models. While the k-coverage probabilities correspond to the marginal distributions of the order statistics of the SINR process, a more general relation is presented connecting the Factorial Moment measures of the SINR process to the joint densities of these order statistics. This gives a way for calculating exact values of the coverage probabilities arising in a general scenario of signal combination and interference cancellation between base stations. The presented framework consisting of mathematical representations of SINR characteristics with respect to the Factorial Moment measures holds for the whole domain of SINR and is amenable to considerable model extension.
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Studying the SINR Process of the Typical User in Poisson Networks Using Its Factorial Moment Measures
IEEE Transactions on Information Theory, 2015Co-Authors: Bartlomiej Blaszczyszyn, Holger Paul KeelerAbstract:International audienceBased on a stationary Poisson point process, a wireless network model with random propagation effects (shadowing and/or fading) is considered in order to examine the process formed by the signal-to-interference-plus-noise ratio (SINR) values experienced by a typical user with respect to all base stations in the down-link channel. This SINR process is completely characterized by deriving its Factorial Moment measures, which involve numerically tractable, explicit integral expressions. This novel framework naturally leads to expressions for the k-coverage probability, including the case of random SINR threshold values considered in multi-tier network models. While the k-coverage probabilities correspond to the marginal distributions of the order statistics of the SINR process, a more general relation is presented connecting the Factorial Moment measures of the SINR process to the joint densities of these order statistics. This gives a way for calculating exact values of the coverage probabilities arising in a general scenario of signal combination and interference cancellation between base stations. The presented framework consisting of mathematical representations of SINR characteristics with respect to the Factorial Moment measures holds for the whole domain of SINR and is amenable to considerable model extension
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A note on expansion for functionals of spatial marked point processes
Statistics & Probability Letters, 1997Co-Authors: Bartlomiej Blaszczyszyn, Ely Merzbach, Volker SchmidtAbstract:Expansion of the mean value of a functional of a spatial marked point process with respect to the Factorial Moment measures is presented. This paper complements previous studies of a point process on the real line, by extending the results to a general Polish space.
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Factorial Moment expansion for stochastic systems
Stochastic Processes and their Applications, 1995Co-Authors: Bartlomiej BlaszczyszynAbstract:Abstract For a given functional of a simple point process, we find an analogue of Taylor's theorem for its mean value. The terms of the expansion are integrals of some real functions with respect to Factorial Moment measures of the point process. The remainder term is an integral of some functional with respect to a higher order Campbell measure. A special case of this expansion is Palm-Khinchin formula. The results complement previous studies of Reiman and Simon (1989), Baccelli and Bremaud (1993) and shed new light on light traffic approximations of Daley and Rolski (1994), Blaszczyszyn and Rolski (1993).
Holger Paul Keeler - One of the best experts on this subject based on the ideXlab platform.
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Studying the SINR Process of the Typical User in Poisson Networks Using Its Factorial Moment Measures
IEEE Transactions on Information Theory, 2015Co-Authors: Bartlomiej Blaszczyszyn, Holger Paul KeelerAbstract:Based on a stationary Poisson point process, a wireless network model with random propagation effects (shadowing and/or fading) is considered in order to examine the process formed by the signal-to-interference-plus-noise ratio (SINR) values experienced by a typical user with respect to all base stations in the down-link channel. This SINR process is completely characterized by deriving its Factorial Moment measures, which involve numerically tractable, explicit integral expressions. This novel framework naturally leads to expressions for the k-coverage probability, including the case of random SINR threshold values considered in multi-tier network models. While the k-coverage probabilities correspond to the marginal distributions of the order statistics of the SINR process, a more general relation is presented connecting the Factorial Moment measures of the SINR process to the joint densities of these order statistics. This gives a way for calculating exact values of the coverage probabilities arising in a general scenario of signal combination and interference cancellation between base stations. The presented framework consisting of mathematical representations of SINR characteristics with respect to the Factorial Moment measures holds for the whole domain of SINR and is amenable to considerable model extension.
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Studying the SINR Process of the Typical User in Poisson Networks Using Its Factorial Moment Measures
IEEE Transactions on Information Theory, 2015Co-Authors: Bartlomiej Blaszczyszyn, Holger Paul KeelerAbstract:International audienceBased on a stationary Poisson point process, a wireless network model with random propagation effects (shadowing and/or fading) is considered in order to examine the process formed by the signal-to-interference-plus-noise ratio (SINR) values experienced by a typical user with respect to all base stations in the down-link channel. This SINR process is completely characterized by deriving its Factorial Moment measures, which involve numerically tractable, explicit integral expressions. This novel framework naturally leads to expressions for the k-coverage probability, including the case of random SINR threshold values considered in multi-tier network models. While the k-coverage probabilities correspond to the marginal distributions of the order statistics of the SINR process, a more general relation is presented connecting the Factorial Moment measures of the SINR process to the joint densities of these order statistics. This gives a way for calculating exact values of the coverage probabilities arising in a general scenario of signal combination and interference cancellation between base stations. The presented framework consisting of mathematical representations of SINR characteristics with respect to the Factorial Moment measures holds for the whole domain of SINR and is amenable to considerable model extension
Dipak Ghosh - One of the best experts on this subject based on the ideXlab platform.
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Ring-Like and Jet-Like Events in Ultra High-Energy Interactions—an Analysis in Terms of Multifractal Parameters
Brazilian Journal of Physics, 2014Co-Authors: Dipak Ghosh, Argha Deb, Mitali Mondal, Aparna Dhar, Soma BiswasAbstract:Ring-like and jet-like events produced in 16O-AgBr interactions at 60 AGeV are analyzed in terms of multifractal G-Moment method and Factorial Moment method in both η space and ϕ space for emitted pions. Further, the Levy indices and multifractal specific heat c have been calculated. The results clearly indicate that μ and c both are different in ring-like and jet-like events depicting different mechanism in the production process.
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Fluctuation Pattern of Shower and Compound Multiplicity Distributions in Nucleus-Nucleus Interactions at a Few GeV
International Journal of Modern Physics E, 2011Co-Authors: Dipak Ghosh, Argha Deb, Swarnapratim Bhattacharyya, Jayita Ghosh, Prabir Kumar Haldar, Madhumita Lahiri, Pasupati Mandal, Subrata Biswas, Dipak MaityAbstract:This work presents a study on the multiplicity distribution of shower and compound multiplicity (pions + target protons) emitted from 12C–AgBr and 24Mg–AgBr interactions at 4.5 AGeV in terms of negative binomial distribution (NBD) and also on the fluctuation pattern of shower and compound multiplicity in the frame work of two-dimensional Factorial Moment methodology using the concept of Hurst exponent.
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SELF-AFFINE SCALING AND NON-THERMAL PHASE TRANSITION IN TARGET FRAGMENTS OF MUON–NUCLEUS INTERACTIONS AT HIGH ENERGY
Modern Physics Letters A, 2007Co-Authors: Dipak Ghosh, Argha Deb, Prabir Kumar Haldar, Syed Imtiaz Ahmed, Parthasarathi GhoshAbstract:In this paper non-thermal phase transition for the target fragments of lepton–nucleus interactions at (420±45) GeV is studied in the framework of two-dimensional Factorial Moment methodology using the concept of Hurst exponent (H) to take care of anisotropic phase space. An indication of non-thermal phase transition is obtained where the anisotropic scaling behavior (self affinity) of dynamical fluctuation is best revealed (H = 0.8).
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Study of multidimensional fluctuations and non-thermal phase transition in ring like and jet like events in ultrarelativistic nuclear collisions
2007Co-Authors: Dipak Ghosh, Argha Deb, Prabir Kumar Haldar, Sima GuptaroyAbstract:S-AgBr interactions at 200 A GeV has been studied. The study has been performed in the frame work of two-dimensional Factorial Moment methodology using the concept of Hurst exponent (H) to take care of anisotropic phase-space. An indication of non-thermal phase transition in jet like events only is revealed by the data.
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FLUCTUATION OF PIONS IN RELATIVISTIC AND ULTRARELATIVISTIC NUCLEAR COLLISIONS - SCALE DEPENDENT OR NOT?
2007Co-Authors: Dipak Ghosh, Argha Deb, Srimonti DuttaAbstract:Fluctuation pattern of pions is investigated in a wide range of projectile energy from 4.5 AGeV ( 24 Mg-AgBr interactions) to 200 AGeV ( 32 S-AgBr interactions). Two-dimensional analysis is performed. To obtain the correct phase-space partition condition considering anisotropy of phase space, we use the concept of Hurst exponent H. The analysis is performed in a rigorous way by fitting one-dimensional Factorial Moment saturation curves. The effective fluctuation strength αeff is calculated. The study reveals that the fluctuation pattern is scale-dependent at both relativistic and ultrarelativistic energies.
P Prieto - One of the best experts on this subject based on the ideXlab platform.
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Autocorrelation evaluation from clipped photon detection.
Optics letters, 1994Co-Authors: Manuel P. Cagigal, P Prieto, L VegaAbstract:We present two new techniques for estimating the autocorrelation function, based on the measurement of the mean number of clipped photocounts and on the calculation of the second-order Factorial Moment of a series of clipped data. The first procedure has the advantage of simplicity, although it produces a poor signal-to-noise ratio. On the other hand, the second technique gives a very good signal-to-noise ratio, when compared with other known methods.
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the second order Factorial Moment of the time interval distribution and its application to life time determination
Optics Communications, 1993Co-Authors: Manuel P. Cagigal, P Prieto, L VegaAbstract:Abstract A Poisson point-process (P.PP) presents a series of characteristics which may be used to define functions with an optimal signal to noise ratio. This paper describes the second-order Factorial Moment of the interval probability distribution, obtained by measuring time-intervals in a P.PP. The advantage of this function is that it can be applied to cases of low light level, in which it is necessary to increase the signal-to-noise ratio. As a particular case of low light level signals, we have applied this method to a real single-photon-decay spectroscopy experiment and measured the life-time of the 4 T 1 state of Mn 2+ in an undoped TMMC crystal at room temperature.
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Evaluation of triple correlation from triggered Factorial Moment measurement.
Optics letters, 1992Co-Authors: Manuel P. Cagigal, P PrietoAbstract:Triple-correlation values are obtained as a combination of second-order Factorial Moments of the triggered photocount distribution. The signal-to-noise ratio obtained from this kind of measurement is smaller than that obtained from direct calculation of the triple correlation for small time-delay values.
