Blind equalisation of multilevel PAM data for nonminimum phase channels via second- and fourth-order cumulants

This paper introduces a new blind equalisation algorithm for the pulse amplitude modulation (PAM) data transmitted through nonminimum phase (NMP) channels. The algorithm itself is based on a noncausal AR model of communication channels and the second- and fourth-order cumulants of the received data series, where only the diagonal slices of cumulants are used. The AR parameters are adjusted at each sample by using a successive over-relaxation (SOR) scheme, a variety of the ordinary LMS scheme, but with a faster convergence rate and a greater robustness to the selection of the ‘step-size’ in iterations. Computer simulations are implemented for both linear time-invariant (LTI) and linear time-variant (LTV) NMP channels, and the results show that the algorithm proposed in this paper has a fast convergence rate and a potential capability to track the LTV NMP channels.

Measurement of flow harmonics with multi-particle cumulants in Pb+Pb collisions at √sNN=2.76 TeV with the ATLAS detector

ATLAS measurements of the azimuthal anisotropy in lead–lead collisions at √sNN = 2.76 TeV are shown using a dataset of approximately 7μb−1 collected at the LHC in 2010. The measurements are performed for charged particles with transversemomenta 0.5 < pT < 20 GeV and in the pseudorapidity range |η| < 2.5. The anisotropy is characterized by the Fourier coefficients, vn, of the charged-particle azimuthal angle distribution for n = 2–4. The Fourier coefficients are evaluated using multi-particle cumulants calculated with the generating function method. Results on the transverse momentum, pseudorapidity and centrality dependence of the vn coefficients are presented. The elliptic flow, v2, is obtained from the two-, four-, six- and eight-particle cumulants while higher-order coefficients, v3 and v4, are determined with two- and four-particle cumulants. Flow harmonics vn measured with four-particle cumulants are significantly reduced compared to the measurement involving two-particle cumulants. A comparison to vn measurements obtained using different analysis methods and previously reported by the LHC experiments is also shown. Results of measurements of flow fluctuations evaluated with multiparticle cumulants are shown as a function of transverse momentum and the collision centrality. Models of the initial spatial geometry and its fluctuations fail to describe the flow fluctuations measurements.

Interference detection in GNSS signals using Gaussianity criterion

We assess the performance of Gaussianity tests, namely the Anscombe-Glynn, Lilliefors, Cramér-von Mises, and Giannakis-Tsatsanis (G-T), with the purpose of detecting narrowband and wideband interference in GNSS signals. Simulations have shown that the G-T test outperforms the others being suitable as a benchmark for comparison with different types of interference detection algorithms. © 2014 EURASIP.

Integrated random processes exhibiting long tails, finite moments, and power-law spectra

A dynamical model based on a continuous addition of colored shot noises is presented. The resulting process is colored and non-Gaussian. A general expression for the characteristic function of the process is obtained, which, after a scaling assumption, takes on a form that is the basis of the results derived in the rest of the paper. One of these is an expansion for the cumulants, which are all finite, subject to mild conditions on the functions defining the process. This is in contrast with the Lévy distribution¿which can be obtained from our model in certain limits¿which has no finite moments. The evaluation of the spectral density and the form of the probability density function in the tails of the distribution shows that the model exhibits a power-law spectrum and long tails in a natural way. A careful analysis of the characteristic function shows that it may be separated into a part representing a Lévy process together with another part representing the deviation of our model from the Lévy process. This

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

On cumulant techniques in speech processing

This paper analyzes applications of cumulant analysis in speech processing. A special focus is made on different second-order statistics. A dominant role is played by an integral representation for cumulants by means of integrals involving cyclic products of kernels.

Bootstrapping high frequency data

Nous développons dans cette thèse, des méthodes de bootstrap pour les données financières de hautes fréquences. Les deux premiers essais focalisent sur les méthodes de bootstrap appliquées à l’approche de "pré-moyennement" et robustes à la présence d’erreurs de microstructure. Le "pré-moyennement" permet de réduire l’influence de l’effet de microstructure avant d’appliquer la volatilité réalisée. En se basant sur cette ap- proche d’estimation de la volatilité intégrée en présence d’erreurs de microstructure, nous développons plusieurs méthodes de bootstrap qui préservent la structure de dépendance et l’hétérogénéité dans la moyenne des données originelles. Le troisième essai développe une méthode de bootstrap sous l’hypothèse de Gaussianité locale des données financières de hautes fréquences. Le premier chapitre est intitulé: "Bootstrap inference for pre-averaged realized volatility based on non-overlapping returns". Nous proposons dans ce chapitre, des méthodes de bootstrap robustes à la présence d’erreurs de microstructure. Particulièrement nous nous sommes focalisés sur la volatilité réalisée utilisant des rendements "pré-moyennés" proposés par Podolskij et Vetter (2009), où les rendements "pré-moyennés" sont construits sur des blocs de rendements à hautes fréquences consécutifs qui ne se chevauchent pas. Le "pré-moyennement" permet de réduire l’influence de l’effet de microstructure avant d’appliquer la volatilité réalisée. Le non-chevauchement des blocs fait que les rendements "pré-moyennés" sont asymptotiquement indépendants, mais possiblement hétéroscédastiques. Ce qui motive l’application du wild bootstrap dans ce contexte. Nous montrons la validité théorique du bootstrap pour construire des intervalles de type percentile et percentile-t. Les simulations Monte Carlo montrent que le bootstrap peut améliorer les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques, pourvu que le choix de la variable externe soit fait de façon appropriée. Nous illustrons ces méthodes en utilisant des données financières réelles. Le deuxième chapitre est intitulé : "Bootstrapping pre-averaged realized volatility under market microstructure noise". Nous développons dans ce chapitre une méthode de bootstrap par bloc basée sur l’approche "pré-moyennement" de Jacod et al. (2009), où les rendements "pré-moyennés" sont construits sur des blocs de rendements à haute fréquences consécutifs qui se chevauchent. Le chevauchement des blocs induit une forte dépendance dans la structure des rendements "pré-moyennés". En effet les rendements "pré-moyennés" sont m-dépendant avec m qui croît à une vitesse plus faible que la taille d’échantillon n. Ceci motive l’application d’un bootstrap par bloc spécifique. Nous montrons que le bloc bootstrap suggéré par Bühlmann et Künsch (1995) n’est valide que lorsque la volatilité est constante. Ceci est dû à l’hétérogénéité dans la moyenne des rendements "pré-moyennés" au carré lorsque la volatilité est stochastique. Nous proposons donc une nouvelle procédure de bootstrap qui combine le wild bootstrap et le bootstrap par bloc, de telle sorte que la dépendance sérielle des rendements "pré-moyennés" est préservée à l’intérieur des blocs et la condition d’homogénéité nécessaire pour la validité du bootstrap est respectée. Sous des conditions de taille de bloc, nous montrons que cette méthode est convergente. Les simulations Monte Carlo montrent que le bootstrap améliore les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques. Nous illustrons cette méthode en utilisant des données financières réelles. Le troisième chapitre est intitulé: "Bootstrapping realized covolatility measures under local Gaussianity assumption". Dans ce chapitre nous montrons, comment et dans quelle mesure on peut approximer les distributions des estimateurs de mesures de co-volatilité sous l’hypothèse de Gaussianité locale des rendements. En particulier nous proposons une nouvelle méthode de bootstrap sous ces hypothèses. Nous nous sommes focalisés sur la volatilité réalisée et sur le beta réalisé. Nous montrons que la nouvelle méthode de bootstrap appliquée au beta réalisé était capable de répliquer les cummulants au deuxième ordre, tandis qu’il procurait une amélioration au troisième degré lorsqu’elle est appliquée à la volatilité réalisée. Ces résultats améliorent donc les résultats existants dans cette littérature, notamment ceux de Gonçalves et Meddahi (2009) et de Dovonon, Gonçalves et Meddahi (2013). Les simulations Monte Carlo montrent que le bootstrap améliore les propriétés en échantillon fini de l’estimateur de la volatilité intégrée par rapport aux résultats asymptotiques et les résultats de bootstrap existants. Nous illustrons cette méthode en utilisant des données financières réelles.

Cumulant-based deconvolution and identification: several new families of linear equations

This paper presents several new families of cumulant-based linear equations with respect to the inverse filter coefficients for deconvolution (equalisation) and identification of nonminimum phase systems. Based on noncausal autoregressive (AR) modeling of the output signals and three theorems, these equations are derived for the cases of 2nd-, 3rd and 4th-order cumulants, respectively, and can be expressed as identical or similar forms. The algorithms constructed from these equations are simpler in form, but can offer more accurate results than the existing methods. Since the inverse filter coefficients are simply the solution of a set of linear equations, their uniqueness can normally be guaranteed. Simulations are presented for the cases of skewed series, unskewed continuous series and unskewed discrete series. The results of these simulations confirm the feasibility and efficiency of the algorithms.

Measurement of the elliptic anisotropy of charged particles produced in PbPb collisions at √sNN=2.76 TeV

The anisotropy of the azimuthal distributions of charged particles produced in √sNN=2.76 TeV PbPb collisions is studied with the CMS experiment at the LHC. The elliptic anisotropy parameter, v2, defined as the second coefficient in a Fourier expansion of the particle invariant yields, is extracted using the event-plane method, two- and four-particle cumulants, and Lee-Yang zeros. The anisotropy is presented as a function of transverse momentum (pT), pseudorapidity (η) over a broad kinematic range, 0.3

What can light scattering spectroscopy do for membrane-active peptide studies

Highly charged peptides are important components of the immune system and belong to an important family of antibiotics. Although their therapeutic activity is known, most of the molecular level mechanisms are controversial. A wide variety of different approaches are usually applied to understand their mechanisms, but light scattering techniques are frequently overlooked. Yet, light scattering is a noninvasive technique that allows insights both on the peptide mechanism of action as well as on the development of new antibiotics. Dynamic light scattering (DLS) and static light scattering (SLS) are used to measure the aggregation process of lipid vesicles upon addition of peptides and molecular properties (shape, molecular weight). The high charge of these peptides allows electrostatic attraction toward charged lipid vesicles, which is studied by zeta potential (zeta-potential) measurements. Copyright (c) 2008 European Peptide Society and John Wiley & Sons, Ltd.

Inclusive charged hadron elliptic flow in Au+Au collisions at root s(NN)=7.7-39 GeV

A systematic study is presented for centrality, transverse momentum (p(T)), and pseudorapidity (eta) dependence of the inclusive charged hadron elliptic flow (v(2)) at midrapidity (vertical bar eta vertical bar < 1.0) in Au + Au collisions at root s(NN) = 7.7, 11.5, 19.6, 27, and 39 GeV. The results obtained with different methods, including correlations with the event plane reconstructed in a region separated by a large pseudorapidity gap and four-particle cumulants (v(2){4}), are presented to investigate nonflow correlations and v(2) fluctuations. We observe that the difference between v(2){2} and v(2){4} is smaller at the lower collision energies. Values of v(2), scaled by the initial coordinate space eccentricity, v(2)/epsilon, as a function of p(T) are larger in more central collisions, suggesting stronger collective flow develops in more central collisions, similar to the results at higher collision energies. These results are compared to measurements at higher energies at the Relativistic Heavy Ion Collider (root s(NN) = 62.4 and 200 GeV) and at the Large Hadron Collider (Pb + Pb collisions at root s(NN) = 2.76 TeV). The v(2)(pT) values for fixed pT rise with increasing collision energy within the pT range studied (<2 GeV/c). A comparison to viscous hydrodynamic simulations is made to potentially help understand the energy dependence of v(2)(pT). We also compare the v(2) results to UrQMD and AMPT transport model calculations, and physics implications on the dominance of partonic versus hadronic phases in the system created at beam energy scan energies are discussed.

Energy and system-size dependence of two- and four-particle nu(2) measurements in heavy-ion collisions at root S-NN=62.4 and 200 GeV and their implications on flow fluctuations and nonflow

We present STAR measurements of azimuthal anisotropy by means of the two- and four-particle cumulants nu(2) (nu(2){2} and nu(2){4}) for Au + Au and Cu + Cu collisions at center-of-mass energies root S-NN = 62.4 and 200 GeV. The difference between nu(2){2}(2) and nu(2){4}(2) is related to nu(2) fluctuations (sigma(nu 2)) and nonflow (delta(2)). We present an upper limit to sigma(nu 2)/nu 2. Following the assumption that eccentricity fluctuations sigma(epsilon) dominate nu(2) fluctuations nu(2)/sigma nu(2) approximate to epsilon/sigma epsilon we deduce the nonflow implied for several models of eccentricity fluctuations that would be required for consistency with nu(2){2} and nu(2){4}. We also present results on the ratio of nu(2) to eccentricity.

Monte Carlo simulations of Potts glasses

A complete understanding of the glass transition isstill a challenging problem. Some researchers attributeit to the (hypothetical) occurrence of a static phasetransition, others emphasize the dynamical transitionof mode coupling-theory from an ergodic to a non ergodicstate. A class of disordered spin models has been foundwhich unifies both scenarios. One of these models isthe p-state infinite range Potts glass with p>4, whichexhibits in the thermodynamic limit both a dynamicalphase transition at a temperature T_D, and a static oneat T_0 < T_D. In this model every spins interacts withall the others, irrespective of distance. Interactionsare taken from a Gaussian distribution.In order to understand better its behavior forfinite number N of spins and the approach to thethermodynamic limit, we have performed extensive MonteCarlo simulations of the p=10 Potts glass up to N=2560.The time-dependent spin-autocorrelation function C(t)shows strong finite size effects and it does not showa plateau even for temperatures around the dynamicalcritical temperature T_D. We show that the N-andT-dependence of the relaxation time for T > T_D can beunderstood by means of a dynamical finite size scalingAnsatz.The behavior in the spin glass phase down to atemperature T=0.7 (about 60% of the transitiontemperature) is studied. Well equilibratedconfigurations are obtained with the paralleltempering method, which is also useful for properlyestablishing static properties, such as the orderparameter distribution function P(q). Evidence is givenfor the compatibility with a one step replica symmetrybreaking scenario. The study of the cumulants of theorder parameter does not permit a reliable estimation ofthe static transition temperature. The autocorrelationfunction at low T exhibits a two-step decay, and ascaling behavior typical of supercooled liquids, thetime-temperature superposition principle, is observed. Inthis region the dynamics is governed by Arrheniusrelaxations, with barriers growing like N^{1/2}.We analyzed the single spin dynamics down to temperaturesmuch lower than the dynamical transition temperature. We found strong dynamical heterogeneities, which explainthe non-exponential character of the spin autocorrelationfunction. The spins seem to relax according to dynamicalclusters. The model in three dimensions tends to acquireferromagnetic order for equal concentration of ferro-and antiferromagnetic bonds. The ordering has differentcharacteristics from the pure ferromagnet. The spinglass susceptibility behaves like chi_{SG} proportionalto 1/T in the region where a spin glass is predicted toexist in mean-field. Also the analysis of the cumulantsis consistent with the absence of spin glass orderingat finite temperature. The dynamics shows multi-scalerelaxations if a bimodal distribution of bonds isused. We propose to understand it with a model based onthe local spin configuration. This is consistent with theabsence of plateaus if Gaussian interactions are used.