Ornstein-Uhlenbeck Processes Simulation
Kuzmina, A.
2012-01-01
In this paper we give a brief introduction to Ornstein-Uhlenbeck processes and their simulation methods. Ornstein-Uhlenbeck processes were introduced by Barndorff-Nielsen and Shephard (2001) as a model to describe volatility in finance. Ornstein-Uhlenbeck processes are based on Levy processes. Levy processes simulation may be found in [1, 2].
Quasi Ornstein-Uhlenbeck processes
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Basse-O'Connor, Andreas
The question of existence and properties of stationary solutions to Langevin equations driven by noise processes with stationary increments is discussed, with particular focus on noise processes of pseudo moving average type. On account of the Wold-Karhunen decomposition theorem such solutions...... of the associated autocorrelation functions, both for small and large lags. Applications to Gaussian and Lévy driven fractional Ornstein-Uhlenbeck processes are presented. As an element in the derivations a Fubini theorem for Lévy bases is established....
Weyl and Riemann-Liouville multifractional Ornstein-Uhlenbeck processes
International Nuclear Information System (INIS)
Lim, S C; Teo, L P
2007-01-01
This paper considers two new multifractional stochastic processes, namely the Weyl multifractional Ornstein-Uhlenbeck process and the Riemann-Liouville multifractional Ornstein-Uhlenbeck process. Basic properties of these processes such as locally self-similar property and Hausdorff dimension are studied. The relationship between the multifractional Ornstein-Uhlenbeck processes and the corresponding multifractional Brownian motions is established
Quasi Ornstein-Uhlenbeck processes
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Basse-O'Connor, Andreas
2011-01-01
The question of existence and properties of stationary solutions to Langevin equations driven by noise processes with stationary increments is discussed, with particular focus on noise processes of pseudo-moving-average type. On account of the Wold–Karhunen decomposition theorem, such solutions are...... of the associated autocorrelation functions, both for small and large lags. Applications to Gaussian- and Lévy-driven fractional Ornstein–Uhlenbeck processes are presented. A Fubini theorem for Lévy bases is established as an element in the derivations....
Spectral properties of superpositions of Ornstein-Uhlenbeck type processes
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Leonenko, N.N.
2005-01-01
Stationary processes with prescribed one-dimensional marginal laws and long-range dependence are constructed. The asymptotic properties of the spectral densities are studied. The possibility of Mittag-Leffler decay in the autocorrelation function of superpositions of Ornstein-Uhlenbeck type...... processes is proved....
Some properties of the fractional Ornstein-Uhlenbeck process
International Nuclear Information System (INIS)
Yan Litan; Lu Yunsheng; Xu Zhiqiang
2008-01-01
We consider the fractional analogue of the Ornstein-Uhlenbeck process, i.e. the solution of the Langevin equation driven by a fractional Brownian motion in place of the usual Brownian motion. We establish some properties of these processes. We show that the process is local nondeterminism. For a two-dimensional process we show that its renormalized self-intersection local time exists in L 2 if and only if 0< H<3/4
Representations of Urbanik's classes and multiparameter Ornstein-Uhlenbeck processes
DEFF Research Database (Denmark)
Graversen, Svend-Erik; Pedersen, Jan
2011-01-01
A class of integrals with respect to homogeneous Lévy bases on Rk is considered. In the one-dimensional case k=1 this class corresponds to the selfdecomposable distributions. Necessary and sufficient conditions for existence as well as some representations of the integrals are given. Generalizing...... the one-dimensional case it is shown that the class of integrals corresponds to Urbanik's class Lk-1(R). Finally, multiparameter Ornstein-Uhlenbeck processes are defined and studied....
Ergodicity and Parameter Estimates for Infinite-Dimensional Fractional Ornstein-Uhlenbeck Process
International Nuclear Information System (INIS)
Maslowski, Bohdan; Pospisil, Jan
2008-01-01
Existence and ergodicity of a strictly stationary solution for linear stochastic evolution equations driven by cylindrical fractional Brownian motion are proved. Ergodic behavior of non-stationary infinite-dimensional fractional Ornstein-Uhlenbeck processes is also studied. Based on these results, strong consistency of suitably defined families of parameter estimators is shown. The general results are applied to linear parabolic and hyperbolic equations perturbed by a fractional noise
Integrated stationary Ornstein-Uhlenbeck process, and double integral processes
Abundo, Mario; Pirozzi, Enrica
2018-03-01
We find a representation of the integral of the stationary Ornstein-Uhlenbeck (ISOU) process in terms of Brownian motion Bt; moreover, we show that, under certain conditions on the functions f and g , the double integral process (DIP) D(t) = ∫βt g(s) (∫αs f(u) dBu) ds can be thought as the integral of a suitable Gauss-Markov process. Some theoretical and application details are given, among them we provide a simulation formula based on that representation by which sample paths, probability densities and first passage times of the ISOU process are obtained; the first-passage times of the DIP are also studied.
Generalized Ornstein-Uhlenbeck processes and associated self-similar processes
International Nuclear Information System (INIS)
Lim, S C; Muniandy, S V
2003-01-01
We consider three types of generalized Ornstein-Uhlenbeck processes: the stationary process obtained from the Lamperti transformation of fractional Brownian motion, the process with stretched exponential covariance and the process obtained from the solution of the fractional Langevin equation. These stationary Gaussian processes have many common properties, such as the fact that their local covariances share a similar structure and they exhibit identical spectral densities at large frequency limit. In addition, the generalized Ornstein-Uhlenbeck processes can be shown to be local stationary representations of fractional Brownian motion. Two new self-similar Gaussian processes, in addition to fractional Brownian motion, are obtained by applying the (inverse) Lamperti transformation to the generalized Ornstein-Uhlenbeck processes. We study some of the properties of these self-similar processes such as the long-range dependence. We give a simulation of their sample paths based on numerical Karhunan-Loeve expansion
Generalized Ornstein-Uhlenbeck processes and associated self-similar processes
Lim, S C
2003-01-01
We consider three types of generalized Ornstein-Uhlenbeck processes: the stationary process obtained from the Lamperti transformation of fractional Brownian motion, the process with stretched exponential covariance and the process obtained from the solution of the fractional Langevin equation. These stationary Gaussian processes have many common properties, such as the fact that their local covariances share a similar structure and they exhibit identical spectral densities at large frequency limit. In addition, the generalized Ornstein-Uhlenbeck processes can be shown to be local stationary representations of fractional Brownian motion. Two new self-similar Gaussian processes, in addition to fractional Brownian motion, are obtained by applying the (inverse) Lamperti transformation to the generalized Ornstein-Uhlenbeck processes. We study some of the properties of these self-similar processes such as the long-range dependence. We give a simulation of their sample paths based on numerical Karhunan-Loeve expansi...
A note on a representation and calculation of the long-memory Ornstein-Uhlenbeck process
DEFF Research Database (Denmark)
Høg, Esben
1999-01-01
In this paper we analyze the covariance function for a long memory generalization of Ornstein-Uhlenbeck type processes which are the analogues in continuous time of long memory autoregressions of order 1. A Fractional Brownian Motion with drift is a special case. We find the exact expression...
On the time-homogeneous Ornstein-Uhlenbeck process in the foreign exchange rates
da Fonseca, Regina C. B.; Matsushita, Raul Y.; de Castro, Márcio T.; Figueiredo, Annibal
2015-10-01
Since Gaussianity and stationarity assumptions cannot be fulfilled by financial data, the time-homogeneous Ornstein-Uhlenbeck (THOU) process was introduced as a candidate model to describe time series of financial returns [1]. It is an Ornstein-Uhlenbeck (OU) process in which these assumptions are replaced by linearity and time-homogeneity. We employ the OU and THOU processes to analyze daily foreign exchange rates against the US dollar. We confirm that the OU process does not fit the data, while in most cases the first four cumulants patterns from data can be described by the THOU process. However, there are some exceptions in which the data do not follow linearity or time-homogeneity assumptions.
Fractional Ornstein-Uhlenbeck for index prices of FTSE Bursa Malaysia KLCI
Chen, Kho Chia; Bahar, Arifah; Ting, Chee-Ming
2014-07-01
This paper studies the Ornstein-Uhlenbeck model that incorporates long memory stochastic volatility which is known as fractional Ornstein-Uhlenbeck model. The determination of the existence of long range dependence of the index prices of FTSE Bursa Malaysia KLCI is measured by the Hurst exponent. The empirical distribution of unobserved volatility is estimated using the particle filtering method. The performance between fractional Ornstein -Uhlenbeck and standard Ornstein -Uhlenbeck process had been compared. The mean square errors of the fractional Ornstein-Uhlenbeck model indicated that the model describes index prices better than the standard Ornstein-Uhlenbeck process.
International Nuclear Information System (INIS)
Biyajima, M.
1984-01-01
Stochastic backgrounds of the KNO scaling functions given by Buras and Koba and by Barshay and Yamaguchi are investigated. It is found that they are connected with the stochastic Rayleigh process, and the (1+2)- and (1+4)-dimensional Ornstein-Uhlenbeck process. Moreover those KNO scaling functions are transformed into the KNO scaling functions given by the Perina-McGill formula in terms of a nonlinear transformation. Analyses of data by means of them are made. Probability distributions of the former KNO scaling functions are also calculated by the Poisson transformation. (orig.)
DEFF Research Database (Denmark)
Ditlevsen, Susanne Dalager; Ditlevsen, Ove Dalager
2008-01-01
a subjective graphical test of the applicability of the OU process or the Feller process when applied to a reasonably large sample of observed first-passage data. These non-stationary processes have several applications in biomedical research, for example as idealized models of the neuron membrane potential...... random time break through to the material surface and become observable. However, the OU process has as a model of physical phenomena the defect of not being bounded to the negative side. This defect is not present for the Feller process, which therefore may provide a useful modeling alternative...
Construction of a Family of Quantum Ornstein-Uhlenbeck Semigroups
Ki Ko, C
2003-01-01
For a given quasi-free state on the CCR algebra over one dimensional Hilbert space, a family of Markovian semigroups which leave the quasi-free state invariant is constructed by means of noncommutative elliptic operators and Dirichlet forms on von Neumann algebras. The generators (Dirichlet operators) of the semigroups are analyzed and the spectrums together with eigenspaces are found. When restricted to a maximal abelian subalgebra, the semigroups are reduced to a unique Markovian semigroup of classical Ornstein-Uhlenbeck process.
Directory of Open Access Journals (Sweden)
Pérez-Fructuoso, María José
2017-12-01
Full Text Available Este artículo propone un modelo aleatorio en tiempo continuo para calcular el índice de pérdidas desencadenante de los bonos sobre catástrofes a partir de la cuantía declarada de siniestros hasta el momento de su vencimiento. Bajo la hipótesis de que la cuantía total de una catástrofe se define como la suma de la cuantía declarada de siniestros y la cuantía de siniestros pendiente de declarar, modelizamos la dinámica lineal decreciente de esta última cuantía mediante un proceso browniano aditivo o proceso de Ornstein-Uhlenbeck. La cuantía declarada de siniestros, entonces, se obtiene por diferencia entre la cuantía total de los siniestros y la cuantía de siniestros pendiente de declarar. Finalmente, se comprueba la validez del modelo propuesto estimando sus parámetros fundamentales y contrastando la bondad del ajuste realizado sobre una muestra de series de datos de seis inundaciones ocurridas en diferentes localidades españolas propensas a sufrir este tipo de catástrofes. || This paper develops a continuous-time random model of loss index triggers for cat bonds on the basis of the loss amount incurred until their maturity. Assuming that total loss amount due to a catastrophe is defined as the sum of the incurred loss amount plus the incurred-but-not-yet reported loss amount, we model the decreasing linear dynamics of the latter amount by means of an additive Brownian process (or Ornstein Uhlenbeck process; and get the former by the difference between the total loss amount and the incurred-but-not-yet-reported loss amount. Finally, we test the validity of the model by estimating its core parameters and by contrasting the goodness of fit through a data series of six floods occurred in several Spanish cities prone to suffer such kind of catastrophes.
Conducting properties of classical transmission lines with Ornstein-Uhlenbeck type disorder
International Nuclear Information System (INIS)
Lazo, E.; Diez, E.
2011-01-01
In this work we study the behavior of bands of extended states and localized states which appear in classical disordered electrical transmission lines, when we use a ternary map and the Ornstein-Uhlenbeck process to generate the long-range correlated disorder, instead of using the Fourier filtering method. By performing finite-size scaling we obtain the asymptotic value of the map parameter b in the thermodynamic limit in a selected range of values of the parameters γ and C of the Ornstein-Uhlenbeck process. With these data we obtain the phase diagrams which separate the localized states from the extended states. These are the fundamental results of this article. - Highlights: → We study disordered classical transmission lines. → We use the Ornstein-Uhlenbeck process to generate long-range correlated disorder. → We obtain the phase diagram of the transition in the thermodynamic limit.
The Fractional Ornstein-Uhlenbeck Process
DEFF Research Database (Denmark)
Høg, Esben; Frederiksen, Per H.
The paper revisits dynamic term structure models (DTSMs) and proposes a new way in dealing with the limitation of the classical affine models. In particular, this paper expands the flexibility of the DTSMs by applying a fractional Brownian motion as the governing force of the state variable inste...... of the bond is recovered by solving a fractional version of the fundamental bond pricing equation. Besides this theoretical contribution, the paper proposes an estimation methodology based on the Kalman filter approach, which is applied to the US term structure of interest rates....
Stochastic Resonance in Neuronal Network Motifs with Ornstein-Uhlenbeck Colored Noise
Directory of Open Access Journals (Sweden)
Xuyang Lou
2014-01-01
Full Text Available We consider here the effect of the Ornstein-Uhlenbeck colored noise on the stochastic resonance of the feed-forward-loop (FFL network motif. The FFL motif is modeled through the FitzHugh-Nagumo neuron model as well as the chemical coupling. Our results show that the noise intensity and the correlation time of the noise process serve as the control parameters, which have great impacts on the stochastic dynamics of the FFL motif. We find that, with a proper choice of noise intensities and the correlation time of the noise process, the signal-to-noise ratio (SNR can display more than one peak.
On the stochastic pendulum with Ornstein-Uhlenbeck noise
International Nuclear Information System (INIS)
Mallick, Kirone; Marcq, Philippe
2004-01-01
We study a frictionless pendulum subject to multiplicative random noise. Because of destructive interference between the angular displacement of the system and the noise term, the energy fluctuations are reduced when the noise has a non-zero correlation time. We derive the long time behaviour of the pendulum in the case of Ornstein-Uhlenbeck noise by a recursive adiabatic elimination procedure. An analytical expression for the asymptotic probability distribution function of the energy is obtained and the results agree with numerical simulations. Lastly, we compare our method with other approximation schemes
Memory effects on a resonate-and-fire neuron model subjected to Ornstein-Uhlenbeck noise
Paekivi, S.; Mankin, R.; Rekker, A.
2017-10-01
We consider a generalized Langevin equation with an exponentially decaying memory kernel as a model for the firing process of a resonate-and-fire neuron. The effect of temporally correlated random neuronal input is modeled as Ornstein-Uhlenbeck noise. In the noise-induced spiking regime of the neuron, we derive exact analytical formulas for the dependence of some statistical characteristics of the output spike train, such as the probability distribution of the interspike intervals (ISIs) and the survival probability, on the parameters of the input stimulus. Particularly, on the basis of these exact expressions, we have established sufficient conditions for the occurrence of memory-time-induced transitions between unimodal and multimodal structures of the ISI density and a critical damping coefficient which marks a dynamical transition in the behavior of the system.
Bai, Zhan-Wu; Zhang, Wei
2018-01-01
The diffusion behaviors of Brownian particles in a tilted periodic potential under the influence of an internal white noise and an external Ornstein-Uhlenbeck noise are investigated through numerical simulation. In contrast to the case when the bias force is smaller or absent, the diffusion coefficient exhibits a nonmonotonic dependence on the correlation time of the external noise when bias force is large. A mechanism different from locked-to-running transition theory is presented for the diffusion enhancement by a bias force in intermediate to large damping. In the underdamped regime and the presence of external noise, the diffusion coefficient is a monotonically decreasing function of low temperature rather than a nonmonotonic function when external noise is absent. The diffusive process undergoes four regimes when bias force approaches but is less than its critical value and noises intensities are small. These behaviors can be attributed to the locked-to-running transition of particles.
Breed, Greg A; Golson, Emily A; Tinker, M Tim
2017-01-01
The home-range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home-range model that can accommodate multiple home-range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home-range centers and move among them with some estimable probability. Movement in and around home-range centers is governed by a two-dimensional Ornstein-Uhlenbeck process, while transitions between centers are modeled as a stochastic state-switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home-range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein-Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home-range centers. Females were less likely to move between home-range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex
Estimation of stochastic volatility by using Ornstein-Uhlenbeck type models
Mariani, Maria C.; Bhuiyan, Md Al Masum; Tweneboah, Osei K.
2018-02-01
In this study, we develop a technique for estimating the stochastic volatility (SV) of a financial time series by using Ornstein-Uhlenbeck type models. Using the daily closing prices from developed and emergent stock markets, we conclude that the incorporation of stochastic volatility into the time varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. Furthermore, our estimation algorithm is feasible with large data sets and have good convergence properties.
Randomness and variability of the neuronal activity described by the Ornstein-Uhlenbeck model
Czech Academy of Sciences Publication Activity Database
Košťál, Lubomír; Lánský, Petr; Zucca, Ch.
2007-01-01
Roč. 18, č. 1 (2007), s. 63-75 ISSN 0954-898X R&D Projects: GA MŠk(CZ) LC554; GA AV ČR(CZ) 1ET400110401; GA AV ČR(CZ) KJB100110701 Grant - others:MIUR(IT) PRIN-Cofin 2005 Institutional research plan: CEZ:AV0Z50110509 Keywords : Ornstein-Uhlenbeck * entropy * randomness Subject RIV: FH - Neurology Impact factor: 1.385, year: 2007
A cautionary note on the use of Ornstein Uhlenbeck models in macroevolutionary studies.
Cooper, Natalie; Thomas, Gavin H; Venditti, Chris; Meade, Andrew; Freckleton, Rob P
2016-05-01
Phylogenetic comparative methods are increasingly used to give new insights into the dynamics of trait evolution in deep time. For continuous traits the core of these methods is a suite of models that attempt to capture evolutionary patterns by extending the Brownian constant variance model. However, the properties of these models are often poorly understood, which can lead to the misinterpretation of results. Here we focus on one of these models - the Ornstein Uhlenbeck (OU) model. We show that the OU model is frequently incorrectly favoured over simpler models when using Likelihood ratio tests, and that many studies fitting this model use datasets that are small and prone to this problem. We also show that very small amounts of error in datasets can have profound effects on the inferences derived from OU models. Our results suggest that simulating fitted models and comparing with empirical results is critical when fitting OU and other extensions of the Brownian model. We conclude by making recommendations for best practice in fitting OU models in phylogenetic comparative analyses, and for interpreting the parameters of the OU model.
Energy Technology Data Exchange (ETDEWEB)
Keanini, R.G.; Srivastava, N.; Tkacik, P.T. [Department of Mechanical Engineering, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28078 (United States); Weggel, D.C. [Department of Civil and Environmental Engineering, University of North Carolina at Charlotte, 9201 University City Blvd., Charlotte, NC 28078 (United States); Knight, P.D. [Mitchell Aerospace and Engineering, Statesville, North Carolina 28677 (United States)
2011-06-15
A long-standing, though ill-understood problem in rocket dynamics, rocket response to random, altitude-dependent nozzle side-loads, is investigated. Side loads arise during low altitude flight due to random, asymmetric, shock-induced separation of in-nozzle boundary layers. In this paper, stochastic evolution of the in-nozzle boundary layer separation line, an essential feature underlying side load generation, is connected to random, altitude-dependent rotational and translational rocket response via a set of simple analytical models. Separation line motion, extant on a fast boundary layer time scale, is modeled as an Ornstein-Uhlenbeck process. Pitch and yaw responses, taking place on a long, rocket dynamics time scale, are shown to likewise evolve as OU processes. Stochastic, altitude-dependent rocket translational motion follows from linear, asymptotic versions of the full nonlinear equations of motion; the model is valid in the practical limit where random pitch, yaw, and roll rates all remain small. Computed altitude-dependent rotational and translational velocity and displacement statistics are compared against those obtained using recently reported high fidelity simulations [Srivastava, Tkacik, and Keanini, J. Appl. Phys. 108, 044911 (2010)]; in every case, reasonable agreement is observed. As an important prelude, evidence indicating the physical consistency of the model introduced in the above article is first presented: it is shown that the study's separation line model allows direct derivation of experimentally observed side load amplitude and direction densities. Finally, it is found that the analytical models proposed in this paper allow straightforward identification of practical approaches for: (i) reducing pitch/yaw response to side loads, and (ii) enhancing pitch/yaw damping once side loads cease. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Breed, Greg A.; Golson, Emily A.; Tinker, M. Tim
2017-01-01
The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful
Simple simulation schemes for CIR and Wishart processes
DEFF Research Database (Denmark)
Pisani, Camilla
2013-01-01
We develop some simple simulation algorithms for CIR and Wishart processes. The main idea is the splitting of their generator into the sum of the square of an Ornstein-Uhlenbeck matrix process and a deterministic process. Joint work with Paolo Baldi, Tor Vergata University, Rome...
Learning for Nonstationary Dirichlet Processes
Czech Academy of Sciences Publication Activity Database
Quinn, A.; Kárný, Miroslav
2007-01-01
Roč. 21, č. 10 (2007), s. 827-855 ISSN 0890-6327 R&D Projects: GA AV ČR 1ET100750401 Grant - others:MŠk ČR(CZ) 2C06001 Program:2C Institutional research plan: CEZ:AV0Z10750506 Keywords : Nestacionární procesy * učení * Dirichletovy procesy * zapomínání Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.776, year: 2007 http://library.utia.cas.cz/separaty/2007/as/karny- learning for nonstationary dirichlet processes.pdf
Results of nonlinear and nonstationary image processing
International Nuclear Information System (INIS)
Pizer, S.M.; Correla, J.A.; Chesler, D.A.; Metz, C.E.
1973-01-01
A nonstationary method, multiple z-divided filtering, and a nonlinear method, biased smearing have been applied to scintigrams. Biased smearing does not appear to hold much promise. Multiple z-divided filtering, on the other hand, appears to be justified, and initial results at minimum encourage further research into the possibility that this technique may become a method of choice
A bootstrap invariance principle for highly nonstationary long memory processes
Kapetanios, George
2004-01-01
This paper presents an invariance principle for highly nonstationary long memory processes, defined as processes with long memory parameter lying in (1, 1.5). This principle provides the tools for showing asymptotic validity of the bootstrap in the context of such processes.
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-01-01
-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters
Reduced equations of motion for quantum systems driven by diffusive Markov processes.
Sarovar, Mohan; Grace, Matthew D
2012-09-28
The expansion of a stochastic Liouville equation for the coupled evolution of a quantum system and an Ornstein-Uhlenbeck process into a hierarchy of coupled differential equations is a useful technique that simplifies the simulation of stochastically driven quantum systems. We expand the applicability of this technique by completely characterizing the class of diffusive Markov processes for which a useful hierarchy of equations can be derived. The expansion of this technique enables the examination of quantum systems driven by non-Gaussian stochastic processes with bounded range. We present an application of this extended technique by simulating Stark-tuned Förster resonance transfer in Rydberg atoms with nonperturbative position fluctuations.
Theoretical analysis of radiographic images by nonstationary Poisson processes
International Nuclear Information System (INIS)
Tanaka, Kazuo; Uchida, Suguru; Yamada, Isao.
1980-01-01
This paper deals with the noise analysis of radiographic images obtained in the usual fluorescent screen-film system. The theory of nonstationary Poisson processes is applied to the analysis of the radiographic images containing the object information. The ensemble averages, the autocorrelation functions, and the Wiener spectrum densities of the light-energy distribution at the fluorescent screen and of the film optical-density distribution are obtained. The detection characteristics of the system are evaluated theoretically. Numerical examples one-dimensional image are shown and the results are compared with those obtained under the assumption that the object image is related to the background noise by the additive process. (author)
International Nuclear Information System (INIS)
Chen, Yong; Ge, Hao; Xiong, Jie; Xu, Lihu
2016-01-01
Fluctuation theorem is one of the major achievements in the field of nonequilibrium statistical mechanics during the past two decades. There exist very few results for steady-state fluctuation theorem of sample entropy production rate in terms of large deviation principle for diffusion processes due to the technical difficulties. Here we give a proof for the steady-state fluctuation theorem of a diffusion process in magnetic fields, with explicit expressions of the free energy function and rate function. The proof is based on the Karhunen-Loève expansion of complex-valued Ornstein-Uhlenbeck process.
Wavelet-Based Methodology for Evolutionary Spectra Estimation of Nonstationary Typhoon Processes
Directory of Open Access Journals (Sweden)
Guang-Dong Zhou
2015-01-01
Full Text Available Closed-form expressions are proposed to estimate the evolutionary power spectral density (EPSD of nonstationary typhoon processes by employing the wavelet transform. Relying on the definition of the EPSD and the concept of the wavelet transform, wavelet coefficients of a nonstationary typhoon process at a certain time instant are interpreted as the Fourier transform of a new nonstationary oscillatory process, whose modulating function is equal to the modulating function of the nonstationary typhoon process multiplied by the wavelet function in time domain. Then, the EPSD of nonstationary typhoon processes is deduced in a closed form and is formulated as a weighted sum of the squared moduli of time-dependent wavelet functions. The weighted coefficients are frequency-dependent functions defined by the wavelet coefficients of the nonstationary typhoon process and the overlapping area of two shifted wavelets. Compared with the EPSD, defined by a sum of the squared moduli of the wavelets in frequency domain in literature, this paper provides an EPSD estimation method in time domain. The theoretical results are verified by uniformly modulated nonstationary typhoon processes and non-uniformly modulated nonstationary typhoon processes.
DEFF Research Database (Denmark)
Harrod, Steven; Kelton, W. David
2006-01-01
Nonstationary Poisson processes are appropriate in many applications, including disease studies, transportation, finance, and social policy. The authors review the risks of ignoring nonstationarity in Poisson processes and demonstrate three algorithms for generation of Poisson processes...
Cappell, M S; Spray, D C; Bennett, M V
1988-06-28
Protractor muscles in the gastropod mollusc Navanax inermis exhibit typical spontaneous miniature end plate potentials with mean amplitude 1.71 +/- 1.19 (standard deviation) mV. The evoked end plate potential is quantized, with a quantum equal to the miniature end plate potential amplitude. When their rate is stationary, occurrence of miniature end plate potentials is a random, Poisson process. When non-stationary, spontaneous miniature end plate potential occurrence is a non-stationary Poisson process, a Poisson process with the mean frequency changing with time. This extends the random Poisson model for miniature end plate potentials to the frequently observed non-stationary occurrence. Reported deviations from a Poisson process can sometimes be accounted for by the non-stationary Poisson process and more complex models, such as clustered release, are not always needed.
Directory of Open Access Journals (Sweden)
Orlov Alexey
2016-01-01
Full Text Available This article presents results of development of the mathematical model of nonstationary separation processes occurring in gas centrifuge cascades for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of germanium isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary separation processes in gas centrifuge cascades for separation of multicomponent isotope mixtures.
Orlov Alexey; Ushakov Anton; Sovach Victor
2016-01-01
This article presents results of development of the mathematical model of nonstationary separation processes occurring in gas centrifuge cascades for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of germanium isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary separation processes in gas centrifuge casca...
Orlov, Aleksey Alekseevich; Ushakov, Anton; Sovach, Victor
2017-01-01
The article presents results of development of a mathematical model of nonstationary hydraulic processes in gas centrifuge cascade for separation of multicomponent isotope mixtures. This model was used for the calculation parameters of gas centrifuge cascade for separation of silicon isotopes. Comparison of obtained values with results of other authors revealed that developed mathematical model is adequate to describe nonstationary hydraulic processes in gas centrifuge cascades for separation...
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Stelzer, Robert
Univariate superpositions of Ornstein-Uhlenbeck (OU) type processes, called supOU processes, provide a class of continuous time processes capable of exhibiting long memory behaviour. This paper introduces multivariate supOU processes and gives conditions for their existence and finiteness...... of moments. Moreover, the second order moment structure is explicitly calculated, and examples exhibit the possibility of long range dependence. Our supOU processes are defined via homogeneous and factorisable Lévy bases. We show that the behaviour of supOU processes is particularly nice when the mean...... reversion parameter is restricted to normal matrices and especially to strictly negative definite ones.For finite variation Lévy bases we are able to give conditions for supOU processes to have locally bounded càdlàg paths of finite variation and to show an analogue of the stochastic differential equation...
Mixtures in nonstable Levy processes
International Nuclear Information System (INIS)
Petroni, N Cufaro
2007-01-01
We analyse the Levy processes produced by means of two interconnected classes of nonstable, infinitely divisible distribution: the variance gamma and the Student laws. While the variance gamma family is closed under convolution, the Student one is not: this makes its time evolution more complicated. We prove that-at least for one particular type of Student processes suggested by recent empirical results, and for integral times-the distribution of the process is a mixture of other types of Student distributions, randomized by means of a new probability distribution. The mixture is such that along the time the asymptotic behaviour of the probability density functions always coincide with that of the generating Student law. We put forward the conjecture that this can be a general feature of the Student processes. We finally analyse the Ornstein-Uhlenbeck process driven by our Levy noises and show a few simulations of it
Noise Diagnostics of Stationary and Non-Stationary Reactor Processes
Energy Technology Data Exchange (ETDEWEB)
Sunde, Carl
2007-04-15
This thesis concerns the application of noise diagnostics on different problems in the area of reactor physics involving both stationary and non-stationary core processes. Five different problems are treated, divided into three different parts. The first problem treated in the first part is the classification of two-phase flow regimes from neutron radiographic and visible light images with a neuro-wavelet algorithm. The algorithm consists of wavelet pre-processing and of an artificial neural network. The result indicates that the wavelet pre-processing is improving the training of the neural network. Next, detector tubes which are suspected of impacting on nearby fuel-assemblies in a boiling water reactor (BWR) are identified by both a classical spectral method and wavelet-based methods. It was found that there is good agreement between the different methods as well as with visual inspections of detector tube and fuel assembly damage made during the outage at the plant. The third problem addresses the determination of the decay ratio of a BWR from the auto-correlation function (ACF). Here wavelets are used, with some success, both for de-trending and de-nosing of the ACF and also for direct estimation of the decay ratio from the ACF. The second part deals with the analysis of beam-mode and shell-mode core-barrel vibrations in pressurised water reactors (PWRs). The beam-mode vibrations are analysed by using parameters of the vibration peaks, in spectra from ex core detectors. A trend analysis of the peak amplitude shows that the peak amplitude is changing during the fuel cycle. When it comes to the analysis of the shell-mode vibration, 1-D analytical and numerical calculations are performed in order to calculate the neutron noise induced in the core. The two calculations are in agreement and show that a large local noise component is present in the core which could be used to classify the shell-mode vibrations. However, a measurement made in the PWR Ringhals-3 shows
Noise Diagnostics of Stationary and Non-Stationary Reactor Processes
International Nuclear Information System (INIS)
Sunde, Carl
2007-01-01
This thesis concerns the application of noise diagnostics on different problems in the area of reactor physics involving both stationary and non-stationary core processes. Five different problems are treated, divided into three different parts. The first problem treated in the first part is the classification of two-phase flow regimes from neutron radiographic and visible light images with a neuro-wavelet algorithm. The algorithm consists of wavelet pre-processing and of an artificial neural network. The result indicates that the wavelet pre-processing is improving the training of the neural network. Next, detector tubes which are suspected of impacting on nearby fuel-assemblies in a boiling water reactor (BWR) are identified by both a classical spectral method and wavelet-based methods. It was found that there is good agreement between the different methods as well as with visual inspections of detector tube and fuel assembly damage made during the outage at the plant. The third problem addresses the determination of the decay ratio of a BWR from the auto-correlation function (ACF). Here wavelets are used, with some success, both for de-trending and de-nosing of the ACF and also for direct estimation of the decay ratio from the ACF. The second part deals with the analysis of beam-mode and shell-mode core-barrel vibrations in pressurised water reactors (PWRs). The beam-mode vibrations are analysed by using parameters of the vibration peaks, in spectra from ex core detectors. A trend analysis of the peak amplitude shows that the peak amplitude is changing during the fuel cycle. When it comes to the analysis of the shell-mode vibration, 1-D analytical and numerical calculations are performed in order to calculate the neutron noise induced in the core. The two calculations are in agreement and show that a large local noise component is present in the core which could be used to classify the shell-mode vibrations. However, a measurement made in the PWR Ringhals-3 shows
Local polynomial Whittle estimation covering non-stationary fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank
to the non-stationary region. By approximating the short-run component of the spectrum by a polynomial, instead of a constant, in a shrinking neighborhood of zero we alleviate some of the bias that the classical local Whittle estimators is prone to. This bias reduction comes at a cost as the variance is in...... study illustrates the performance of the proposed estimator compared to the classical local Whittle estimator and the local polynomial Whittle estimator. The empirical justi.cation of the proposed estimator is shown through an analysis of credit spreads....
International Nuclear Information System (INIS)
Tashchilova, Eh.M.; Sharovarov, G.A.
1985-01-01
The mathematical model of nonstationary processes in heat exchangers with dissociating coolant at supercritical parameters is given. Its dimensionless criteria are deveped. The effect of NPP regenerator parameters on criteria variation is determined. The proceeding nonstationary processes are estimated qualitatively using the dimensionless parameters. Dynamics of the processes in heat exchangers is described by the energy, mass and moment-of-momentum equations for heating and heated medium taking into account heat accumulation in the heat-transfer wall and distribution of parameters along the length of a heat exchanger
Maximum likelihood estimation for integrated diffusion processes
DEFF Research Database (Denmark)
Baltazar-Larios, Fernando; Sørensen, Michael
We propose a method for obtaining maximum likelihood estimates of parameters in diffusion models when the data is a discrete time sample of the integral of the process, while no direct observations of the process itself are available. The data are, moreover, assumed to be contaminated...... EM-algorithm to obtain maximum likelihood estimates of the parameters in the diffusion model. As part of the algorithm, we use a recent simple method for approximate simulation of diffusion bridges. In simulation studies for the Ornstein-Uhlenbeck process and the CIR process the proposed method works...... by measurement errors. Integrated volatility is an example of this type of observations. Another example is ice-core data on oxygen isotopes used to investigate paleo-temperatures. The data can be viewed as incomplete observations of a model with a tractable likelihood function. Therefore we propose a simulated...
Neural network connectivity and response latency modelled by stochastic processes
DEFF Research Database (Denmark)
Tamborrino, Massimiliano
is connected to thousands of other neurons. The rst question is: how to model neural networks through stochastic processes? A multivariate Ornstein-Uhlenbeck process, obtained as a diffusion approximation of a jump process, is the proposed answer. Obviously, dependencies between neurons imply dependencies......Stochastic processes and their rst passage times have been widely used to describe the membrane potential dynamics of single neurons and to reproduce neuronal spikes, respectively.However, cerebral cortex in human brains is estimated to contain 10-20 billions of neurons and each of them...... between their spike times. Therefore, the second question is: how to detect neural network connectivity from simultaneously recorded spike trains? Answering this question corresponds to investigate the joint distribution of sequences of rst passage times. A non-parametric method based on copulas...
Poplová, Michaela; Sovka, Pavel; Cifra, Michal
2017-01-01
Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.
Matérn-based nonstationary cross-covariance models for global processes
Jun, Mikyoung
2014-07-01
Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible cross-covariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-dependences between them and also for improved predictions. We propose various ways to produce cross-covariance models, based on the Matérn covariance model class, that are suitable for describing prominent nonstationary characteristics of the global processes. In particular, we seek nonstationary versions of Matérn covariance models whose smoothness parameters vary over space, coupled with a differential operators approach for modeling large-scale nonstationarity. We compare their performance to the performance of some existing models in terms of the aic and spatial predictions in two applications: joint modeling of surface temperature and precipitation, and joint modeling of errors in climate model ensembles. © 2014 Elsevier Inc.
Distinguishing Stationary/Nonstationary Scaling Processes Using Wavelet Tsallis q-Entropies
Directory of Open Access Journals (Sweden)
Julio Ramirez Pacheco
2012-01-01
Full Text Available Classification of processes as stationary or nonstationary has been recognized as an important and unresolved problem in the analysis of scaling signals. Stationarity or nonstationarity determines not only the form of autocorrelations and moments but also the selection of estimators. In this paper, a methodology for classifying scaling processes as stationary or nonstationary is proposed. The method is based on wavelet Tsallis q-entropies and particularly on the behaviour of these entropies for scaling signals. It is demonstrated that the observed wavelet Tsallis q-entropies of 1/f signals can be modeled by sum-cosh apodizing functions which allocates constant entropies to a set of scaling signals and varying entropies to the rest and that this allocation is controlled by q. The proposed methodology, therefore, differentiates stationary signals from non-stationary ones based on the observed wavelet Tsallis entropies for 1/f signals. Experimental studies using synthesized signals confirm that the proposed method not only achieves satisfactorily classifications but also outperforms current methods proposed in the literature.
Non-stationary probabilities for the asymmetric exclusion process on ...
Indian Academy of Sciences (India)
rich picture of relaxation processes which provides an extension of notions of equi- librium statistical mechanics such as phase transitions and spontaneous symmetry breaking to the non-equilibrium case. The asymmetric exclusion process (ASEP) is the simplest model of non-equilibrium theory of many interacting particles ...
On diffusion processes with variable drift rates as models for decision making during learning
International Nuclear Information System (INIS)
Eckhoff, P; Holmes, P; Law, C; Connolly, P M; Gold, J I
2008-01-01
We investigate Ornstein-Uhlenbeck and diffusion processes with variable drift rates as models of evidence accumulation in a visual discrimination task. We derive power-law and exponential drift-rate models and characterize how parameters of these models affect the psychometric function describing performance accuracy as a function of stimulus strength and viewing time. We fit the models to psychophysical data from monkeys learning the task to identify parameters that best capture performance as it improves with training. The most informative parameter was the overall drift rate describing the signal-to-noise ratio of the sensory evidence used to form the decision, which increased steadily with training. In contrast, secondary parameters describing the time course of the drift during motion viewing did not exhibit steady trends. The results indicate that relatively simple versions of the diffusion model can fit behavior over the course of training, thereby giving a quantitative account of learning effects on the underlying decision process
Non-stationary probabilities for the asymmetric exclusion process
Indian Academy of Sciences (India)
A solution of the master equation for a system of interacting particles for finite time and particle density is presented. By using a new form of the Bethe ansatz, the totally asymmetric exclusion process on a ring is solved for arbitrary initial conditions and time intervals.
Nonstationary random acoustic and electromagnetic fields as wave diffusion processes
International Nuclear Information System (INIS)
Arnaut, L R
2007-01-01
We investigate the effects of relatively rapid variations of the boundaries of an overmoded cavity on the stochastic properties of its interior acoustic or electromagnetic field. For quasi-static variations, this field can be represented as an ideal incoherent and statistically homogeneous isotropic random scalar or vector field, respectively. A physical model is constructed showing that the field dynamics can be characterized as a generalized diffusion process. The Langevin-It o-hat and Fokker-Planck equations are derived and their associated statistics and distributions for the complex analytic field, its magnitude and energy density are computed. The energy diffusion parameter is found to be proportional to the square of the ratio of the standard deviation of the source field to the characteristic time constant of the dynamic process, but is independent of the initial energy density, to first order. The energy drift vanishes in the asymptotic limit. The time-energy probability distribution is in general not separable, as a result of nonstationarity. A general solution of the Fokker-Planck equation is obtained in integral form, together with explicit closed-form solutions for several asymptotic cases. The findings extend known results on statistics and distributions of quasi-stationary ideal random fields (pure diffusions), which are retrieved as special cases
A non-Gaussian Ornstein-Uhlenbeck model for pricing wind power futures
DEFF Research Database (Denmark)
Benth, Fred Espen; Pircalabu, Anca
2018-01-01
generated assuming a recent level of installed capacity. Also, based on one year of observed prices for wind power futures with different delivery periods, we study the market price of risk. Generally, we find a negative risk premium whose magnitude decreases as the length of the delivery period increases....
Goychuk, I
2001-08-01
Stochastic resonance in a simple model of information transfer is studied for sensory neurons and ensembles of ion channels. An exact expression for the information gain is obtained for the Poisson process with the signal-modulated spiking rate. This result allows one to generalize the conventional stochastic resonance (SR) problem (with periodic input signal) to the arbitrary signals of finite duration (nonstationary SR). Moreover, in the case of a periodic signal, the rate of information gain is compared with the conventional signal-to-noise ratio. The paper establishes the general nonequivalence between both measures notwithstanding their apparent similarity in the limit of weak signals.
Bayesian soft X-ray tomography using non-stationary Gaussian Processes
International Nuclear Information System (INIS)
Li, Dong; Svensson, J.; Thomsen, H.; Werner, A.; Wolf, R.; Medina, F.
2013-01-01
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods
Bayesian soft X-ray tomography using non-stationary Gaussian Processes
Li, Dong; Svensson, J.; Thomsen, H.; Medina, F.; Werner, A.; Wolf, R.
2013-08-01
In this study, a Bayesian based non-stationary Gaussian Process (GP) method for the inference of soft X-ray emissivity distribution along with its associated uncertainties has been developed. For the investigation of equilibrium condition and fast magnetohydrodynamic behaviors in nuclear fusion plasmas, it is of importance to infer, especially in the plasma center, spatially resolved soft X-ray profiles from a limited number of noisy line integral measurements. For this ill-posed inversion problem, Bayesian probability theory can provide a posterior probability distribution over all possible solutions under given model assumptions. Specifically, the use of a non-stationary GP to model the emission allows the model to adapt to the varying length scales of the underlying diffusion process. In contrast to other conventional methods, the prior regularization is realized in a probability form which enhances the capability of uncertainty analysis, in consequence, scientists who concern the reliability of their results will benefit from it. Under the assumption of normally distributed noise, the posterior distribution evaluated at a discrete number of points becomes a multivariate normal distribution whose mean and covariance are analytically available, making inversions and calculation of uncertainty fast. Additionally, the hyper-parameters embedded in the model assumption can be optimized through a Bayesian Occam's Razor formalism and thereby automatically adjust the model complexity. This method is shown to produce convincing reconstructions and good agreements with independently calculated results from the Maximum Entropy and Equilibrium-Based Iterative Tomography Algorithm methods.
International Nuclear Information System (INIS)
Blinkov, V.N.
1993-01-01
This paper presents a mathematical model and a open-quotes fastclose quotes computer program for analyzing nonstationary thermohydrodynamic processes in distributed multi-element circuits containing a two-phase coolant. The author's approach is based on representing the distributed multi-element circuits with the two-phase coolant (such as cooling circuits of the reactor of an atomic power station) in the form of equivalent thermohydrodynamic chains composed of idealized elements with the intrinsic properties of the structure elements of real systems. The author has developed the nomenclature of such conceptual elements for objects which can be modelled; the nomenclature encompasses the control volumes (with a single-phase or two-phase coolant or a moving boundary of boiling/condensation) and the branch lines (type of tube and connections in dependence on the inertia of the coolant being taken into account) for a hydrodynamic submodel and the thermal components and lines for a thermal submodel. The mathematical models which have been developed and the program using them are designated for various forms of calculating slow thermohydrodynamic processes in multi-element coolant circuits in reactors and modeling test stands. The program facilitates calculation of the range of stable operation, detailed studies of stationary and nonstationary modes of operation, and forecasts of effective engineering measures to obtain stability with the aid of microcomputers
Experimental data processing technique for nonstationary heat transfer on fuel rod simulators
International Nuclear Information System (INIS)
Nikonov, S.P.; Nikonov, A.P.; Belyukin, V.A.
1982-01-01
Non-stationary heat-transfer data processing is considered in connection with experimental studies of the emergency cooling whereat fuel rod imitators both with direct and indirect shell heating were used. The objective of data processing was obtaining the temperature distribution within the imitator, the heat flux removed by the coolant and the shell-coolant heat-transfer coefficient. The special attention was paid to the temperature distribution calculation at the data processing during the reflooding experiments. In this case two factors are assumed to be known: the time dependency of temperature variation at a certain point within the imitator cross-section and the heat flux at some point of the same cross-section. The initial data preparation for calculations, employing the procedure of smoothing by cubic spline functions, is considered as well, with application of an algorithm reported in the literature, which is efficient for the given functional dependency wherein the deviation in each point is known [ru
International Nuclear Information System (INIS)
Yu-Dong, Chen; Li, Li; Yi, Zhang; Jian-Ming, Hu
2009-01-01
In the study of complex networks (systems), the scaling phenomenon of flow fluctuations refers to a certain power-law between the mean flux (activity) (F i ) of the i-th node and its variance σ i as σ i α (F i ) α . Such scaling laws are found to be prevalent both in natural and man-made network systems, but the understanding of their origins still remains limited. This paper proposes a non-stationary Poisson process model to give an analytical explanation of the non-universal scaling phenomenon: the exponent α varies between 1/2 and 1 depending on the size of sampling time window and the relative strength of the external/internal driven forces of the systems. The crossover behaviour and the relation of fluctuation scaling with pseudo long range dependence are also accounted for by the model. Numerical experiments show that the proposed model can recover the multi-scaling phenomenon. (general)
International Nuclear Information System (INIS)
Li, C.; Su, W.; Fang, C.; Zhong, S. J.; Wang, L.
2014-01-01
We present a study of the waiting time distributions (WTDs) of solar energetic particle (SEP) events observed with the spacecraft WIND and GOES. The WTDs of both solar electron events (SEEs) and solar proton events (SPEs) display a power-law tail of ∼Δt –γ . The SEEs display a broken power-law WTD. The power-law index is γ 1 = 0.99 for the short waiting times (<70 hr) and γ 2 = 1.92 for large waiting times (>100 hr). The break of the WTD of SEEs is probably due to the modulation of the corotating interaction regions. The power-law index, γ ∼ 1.82, is derived for the WTD of the SPEs which is consistent with the WTD of type II radio bursts, indicating a close relationship between the shock wave and the production of energetic protons. The WTDs of SEP events can be modeled with a non-stationary Poisson process, which was proposed to understand the waiting time statistics of solar flares. We generalize the method and find that, if the SEP event rate λ = 1/Δt varies as the time distribution of event rate f(λ) = Aλ –α exp (– βλ), the time-dependent Poisson distribution can produce a power-law tail WTD of ∼Δt α –3 , where 0 ≤ α < 2
Directory of Open Access Journals (Sweden)
Robert B. Gramacy
2007-06-01
Full Text Available The tgp package for R is a tool for fully Bayesian nonstationary, semiparametric nonlinear regression and design by treed Gaussian processes with jumps to the limiting linear model. Special cases also implemented include Bayesian linear models, linear CART, stationary separable and isotropic Gaussian processes. In addition to inference and posterior prediction, the package supports the (sequential design of experiments under these models paired with several objective criteria. 1-d and 2-d plotting, with higher dimension projection and slice capabilities, and tree drawing functions (requiring maptree and combinat packages, are also provided for visualization of tgp objects.
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S [Low Temperature Department of the Institute of Solid State Physics of the Bulgarian Academy of Sciences, Sofia
1981-04-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article rests essentially on the ideology of the preceding articles, in particular article I.
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S
1981-04-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article IV rests essentially on the ideology of the preceding articles, in particular article I.
Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.
Shalymov, Dmitry S; Fradkov, Alexander L
2016-01-01
We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.
International Nuclear Information System (INIS)
Shintani, Masanori
1988-01-01
This paper shows that the average and variance of the accumulated damage caused by earthquakes on the piping system attached to a building are related to the seismic response factor λ. The earthquakes refered to in this paper are of a non-stationary random process kind. The average is proportional to λ 2 and the variance to λ 4 . The analytical values of the average and variance for a single-degree-of-freedom system are compared with those obtained from computer simulations. Here the model of the building is a single-degree-of-freedom system. Both average of accumulated damage are approximately equal. The variance obtained from the analysis does not coincide with that from simulations. The reason is considered to be the forced vibraiton by sinusoidal waves, and the sinusoidal waves included random waves. Taking account of amplitude magnification factor, the values of the variance approach those obtained from simulations. (author)
Liao, Yuxi; Li, Hongbao; Zhang, Qiaosheng; Fan, Gong; Wang, Yiwen; Zheng, Xiaoxiang
2014-01-01
Decoding algorithm in motor Brain Machine Interfaces translates the neural signals to movement parameters. They usually assume the connection between the neural firings and movements to be stationary, which is not true according to the recent studies that observe the time-varying neuron tuning property. This property results from the neural plasticity and motor learning etc., which leads to the degeneration of the decoding performance when the model is fixed. To track the non-stationary neuron tuning during decoding, we propose a dual model approach based on Monte Carlo point process filtering method that enables the estimation also on the dynamic tuning parameters. When applied on both simulated neural signal and in vivo BMI data, the proposed adaptive method performs better than the one with static tuning parameters, which raises a promising way to design a long-term-performing model for Brain Machine Interfaces decoder.
McLean, Bryan S; Helgen, Kristofer M; Goodwin, H Thomas; Cook, Joseph A
2018-03-01
Our understanding of mechanisms operating over deep timescales to shape phenotypic diversity often hinges on linking variation in one or few trait(s) to specific evolutionary processes. When distinct processes are capable of similar phenotypic signatures, however, identifying these drivers is difficult. We explored ecomorphological evolution across a radiation of ground-dwelling squirrels whose history includes convergence and constraint, two processes that can yield similar signatures of standing phenotypic diversity. Using four ecologically relevant trait datasets (body size, cranial, mandibular, and molariform tooth shape), we compared and contrasted variation, covariation, and disparity patterns in a new phylogenetic framework. Strong correlations existed between body size and two skull traits (allometry) and among skull traits themselves (integration). Inferred evolutionary modes were also concordant across traits (Ornstein-Uhlenbeck with two adaptive regimes). However, despite these broad similarities, we found divergent dynamics on the macroevolutionary landscape, with phenotypic disparity being differentially shaped by convergence and conservatism. Such among-trait heterogeneity in process (but not always pattern) reiterates the mosaic nature of morphological evolution, and suggests ground squirrel evolution is poorly captured by single process descriptors. Our results also highlight how use of single traits can bias macroevolutionary inference, affirming the importance of broader trait-bases in understanding phenotypic evolutionary dynamics. © 2018 The Author(s). Evolution © 2018 The Society for the Study of Evolution.
Nonstationary statistical theory for multipactor
International Nuclear Information System (INIS)
Anza, S.; Vicente, C.; Gil, J.; Boria, V. E.; Gimeno, B.; Raboso, D.
2010-01-01
This work presents a new and general approach to the real dynamics of the multipactor process: the nonstationary statistical multipactor theory. The nonstationary theory removes the stationarity assumption of the classical theory and, as a consequence, it is able to adequately model electron exponential growth as well as absorption processes, above and below the multipactor breakdown level. In addition, it considers both double-surface and single-surface interactions constituting a full framework for nonresonant polyphase multipactor analysis. This work formulates the new theory and validates it with numerical and experimental results with excellent agreement.
Golubev, Vladimir S.; Banishev, Alexander F.; Azharonok, V. V.; Zabelin, Alexandre M.
1994-09-01
A qualitative analysis of the role of some hydrodynamic flows and instabilities by the process of laser beam-metal sample deep penetration interaction is presented. The forces of vapor pressure, melt surface tension and thermocapillary forces can determined a number of oscillatory and nonstationary phenomena in keyhole and weld pool. Dynamics of keyhole formation in metal plates has been studied under laser beam pulse effect ((lambda) equals 1.06 micrometers ). Velocities of the keyhole bottom motion have been determined at 0.5 X 105 - 106 W/cm2 laser power densities. Oscillatory regime of plate break- down has been found out. Small-dimensional structures with d-(lambda) period was found on the frozen cavity walls, which, in our opinion, can contribute significantly to laser beam absorption. A new form of periodic structure on the frozen pattern being a helix-shaped modulation of the keyhole walls and bottom relief has been revealed. Temperature oscillations related to capillary oscillations in the melt layer were discovered in the cavity. Interaction of the CW CO2 laser beam and the matter by beam penetration into a moving metal sample has been studied. The pulsed and thermodynamic parameters of the surface plasma were investigated by optical and spectroscopic methods. The frequencies of plasma jets pulsations (in 10 - 105 Hz range) are related to possible melt surface instabilities of the keyhole.
Directory of Open Access Journals (Sweden)
Vladimir N. Vodyakov
2017-12-01
Full Text Available Introduction: Mathematical modeling allows assigning optimal parameters for the process of compression molding of plates and calculating the dimensions of the mold without costly and long-term experiments. The options ensure the required precision of pressing. The disadvantages of the known models are the assumptions about the process isothermicity and independence of the thermal-physical coefficients from temperature. The models do not take into account the dependence of the pressure in the cavity of the mold on the excess of the melt; the problem of calculating the dimensions of the mold cavity for given plate dimensions is not posed. The known models do not give a complete description of all stages of the process. The aim of this paper is to develop a perfect mathematical model without limitations for the compression molding of plates from a granulate of highly filled thermoplastic composites. Materials and Methods: The paper proposes a non-stationary mathematical model. The model takes into account the presence of physical states transitions and dependence of the thermophysical characteristics of composites on temperature. The model is based on the known equations of thermal physics and continuum mechanics. Results: Initial and boundary conditions, rheological equations, systems of equations for the material, thermal, and power balance are determined for three stages of the process. The calculation problems are determined too. A program of iterative numerical calculation has been developed because of the resulting system of equations has no analytical solution. A convergence of experimental and theoretical results with the correlation coefficient confirms the adequacy of the developed mathematical model and the calculation program. Discussion and Conclusions: The results of the study allow calculating the dimensions of the mold cavity, the initial granulate required mass, technological losses, the time functions of pressure and temperature
International Nuclear Information System (INIS)
Biyajima, M.; Ide, M.; Mizoguchi, T.; Suzuki, N.
2002-01-01
Recently interesting data on dN ch /dη in Au-Au collisions (η=-ln tan(θ/2)) with the centrality cuts have been reported by PHOBOS and BRAHMS Collaborations. Their data are usually divided by the number of participants (nucleons) in collisions. Instead of this way, using the total multiplicity N ch =∫(dN ch /dη)dη, we find that there are scaling phenomena among (N ch ) -1 dN ch /dη=dn/dη with different centrality cuts at √s NN = 130 GeV and 200 GeV, respectively. To explain these scaling behaviors of dn/dη, we consider the stochastic approach named Ornstein-Uhlenbeck process with two sources. The Langevin equation is adopted for the present explanation. Among dn/dη at 130 GeV and 200 GeV, no significant difference has been found. Possible detection method of the quark-gluon plasma (QGP) through dN ch /dη is presented. (author)
Wavelet analysis for nonstationary signals
International Nuclear Information System (INIS)
Penha, Rosani Maria Libardi da
1999-01-01
Mechanical vibration signals play an important role in anomalies identification resulting of equipment malfunctioning. Traditionally, Fourier spectral analysis is used where the signals are assumed to be stationary. However, occasional transient impulses and start-up process are examples of nonstationary signals that can be found in mechanical vibrations. These signals can provide important information about the equipment condition, as early fault detection. The Fourier analysis can not adequately be applied to nonstationary signals because the results provide data about the frequency composition averaged over the duration of the signal. In this work, two methods for nonstationary signal analysis are used: Short Time Fourier Transform (STFT) and wavelet transform. The STFT is a method of adapting Fourier spectral analysis for nonstationary application to time-frequency domain. To have a unique resolution throughout the entire time-frequency domain is its main limitation. The wavelet transform is a new analysis technique suitable to nonstationary signals, which handles the STFT drawbacks, providing multi-resolution frequency analysis and time localization in a unique time-scale graphic. The multiple frequency resolutions are obtained by scaling (dilatation/compression) the wavelet function. A comparison of the conventional Fourier transform, STFT and wavelet transform is made applying these techniques to: simulated signals, arrangement rotor rig vibration signal and rotate machine vibration signal Hanning window was used to STFT analysis. Daubechies and harmonic wavelets were used to continuos, discrete and multi-resolution wavelet analysis. The results show the Fourier analysis was not able to detect changes in the signal frequencies or discontinuities. The STFT analysis detected the changes in the signal frequencies, but with time-frequency resolution problems. The wavelet continuos and discrete transform demonstrated to be a high efficient tool to detect
Some continual integrals from gaussian forms
International Nuclear Information System (INIS)
Mazmanishvili, A.S.
1985-01-01
The result summary of continual integration of gaussian functional type is given. The summary contains 124 continual integrals which are the mathematical expectation of the corresponding gaussian form by the continuum of random trajectories of four types: real-valued Ornstein-Uhlenbeck process, Wiener process, complex-valued Ornstein-Uhlenbeck process and the stochastic harmonic one. The summary includes both the known continual integrals and the unpublished before integrals. Mathematical results of the continual integration carried in the work may be applied in the problem of the theory of stochastic process, approaching to the finding of mean from gaussian forms by measures generated by the pointed stochastic processes
The stochastic versus the Euclidean approach to quantum fields on a static space-time
International Nuclear Information System (INIS)
De Angelis, G.F.; de Falco, D.
1986-01-01
Equations are presented which modify the definition of the Gaussian field in the Rindler chart in order to make contact with the Wightman state, the Hartle-Hawking state, and the Euclidean field. By taking Ornstein-Uhlenbeck processes the authors have chosen, in the sense of stochastic mechanics, to place precisely the Fulling modes in their harmonic oscillator ground state. In this respect, together with the periodicity of Minkowski space-time, the authors observe that the covariance of the Ornstein-Uhlenbeck process can be obtained by analytical continuation of the Wightman function of the harmonic oscillator at zero temperature
Nonstationary quantum mechanics
International Nuclear Information System (INIS)
Todorov, N.S.
1981-01-01
Some peculiarities of the results of nonstationary perturbation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed. (author)
Yan, Meng; Yao, Minyu; Zhang, Hongming
2005-11-01
The performance of a spectral-phase-encoded (SPE) optical code-division multiple-access (OCDMA) system is analyzed. Regarding the incorrectly decoded signal (IDS) as a nonstationary random process, we derive a novel probability distribution for it. The probability distribution of the IDS is considered a chi-squared distribution with degrees of freedom r=1, which is more reasonable and accurate than in previous work. The bit error rate (BER) of an SPE OCDMA system under multiple-access interference is evaluated. Numerical results show that the system can sustain very low BER even when there are multiple simultaneous users, and as the code length becomes longer or the initial pulse becomes shorter, the system performs better.
Non-parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods
DEFF Research Database (Denmark)
Høg, Esben
In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean-reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...
Non-Parametric Estimation of Diffusion-Paths Using Wavelet Scaling Methods
DEFF Research Database (Denmark)
Høg, Esben
2003-01-01
In continuous time, diffusion processes have been used for modelling financial dynamics for a long time. For example the Ornstein-Uhlenbeck process (the simplest mean--reverting process) has been used to model non-speculative price processes. We discuss non--parametric estimation of these processes...
Evolutionary patterns and processes in the radiation of phyllostomid bats
Directory of Open Access Journals (Sweden)
Monteiro Leandro R
2011-05-01
Full Text Available Abstract Background The phyllostomid bats present the most extensive ecological and phenotypic radiation known among mammal families. This group is an important model system for studies of cranial ecomorphology and functional optimisation because of the constraints imposed by the requirements of flight. A number of studies supporting phyllostomid adaptation have focused on qualitative descriptions or correlating functional variables and diet, but explicit tests of possible evolutionary mechanisms and scenarios for phenotypic diversification have not been performed. We used a combination of morphometric and comparative methods to test hypotheses regarding the evolutionary processes behind the diversification of phenotype (mandible shape and size and diet during the phyllostomid radiation. Results The different phyllostomid lineages radiate in mandible shape space, with each feeding specialisation evolving towards different axes. Size and shape evolve quite independently, as the main directions of shape variation are associated with mandible elongation (nectarivores or the relative size of tooth rows and mandibular processes (sanguivores and frugivores, which are not associated with size changes in the mandible. The early period of phyllostomid diversification is marked by a burst of shape, size, and diet disparity (before 20 Mya, larger than expected by neutral evolution models, settling later to a period of relative phenotypic and ecological stasis. The best fitting evolutionary model for both mandible shape and size divergence was an Ornstein-Uhlenbeck process with five adaptive peaks (insectivory, carnivory, sanguivory, nectarivory and frugivory. Conclusions The radiation of phyllostomid bats presented adaptive and non-adaptive components nested together through the time frame of the family's evolution. The first 10 My of the radiation were marked by strong phenotypic and ecological divergence among ancestors of modern lineages, whereas the
Evolutionary patterns and processes in the radiation of phyllostomid bats
2011-01-01
Background The phyllostomid bats present the most extensive ecological and phenotypic radiation known among mammal families. This group is an important model system for studies of cranial ecomorphology and functional optimisation because of the constraints imposed by the requirements of flight. A number of studies supporting phyllostomid adaptation have focused on qualitative descriptions or correlating functional variables and diet, but explicit tests of possible evolutionary mechanisms and scenarios for phenotypic diversification have not been performed. We used a combination of morphometric and comparative methods to test hypotheses regarding the evolutionary processes behind the diversification of phenotype (mandible shape and size) and diet during the phyllostomid radiation. Results The different phyllostomid lineages radiate in mandible shape space, with each feeding specialisation evolving towards different axes. Size and shape evolve quite independently, as the main directions of shape variation are associated with mandible elongation (nectarivores) or the relative size of tooth rows and mandibular processes (sanguivores and frugivores), which are not associated with size changes in the mandible. The early period of phyllostomid diversification is marked by a burst of shape, size, and diet disparity (before 20 Mya), larger than expected by neutral evolution models, settling later to a period of relative phenotypic and ecological stasis. The best fitting evolutionary model for both mandible shape and size divergence was an Ornstein-Uhlenbeck process with five adaptive peaks (insectivory, carnivory, sanguivory, nectarivory and frugivory). Conclusions The radiation of phyllostomid bats presented adaptive and non-adaptive components nested together through the time frame of the family's evolution. The first 10 My of the radiation were marked by strong phenotypic and ecological divergence among ancestors of modern lineages, whereas the remaining 20 My were
Naseri, H; Homaeinezhad, M R; Pourkhajeh, H
2013-09-01
The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments. Copyright © 2013 Elsevier Ltd. All rights reserved.
On the dependence structure of Gaussian queues
Es-Saghouani, A.; Mandjes, M.R.H.
2009-01-01
In this article we study Gaussian queues (that is, queues fed by Gaussian processes, such as fractional Brownian motion (fBm) and the integrated Ornstein-Uhlenbeck (iOU) process), with a focus on the dependence structure of the workload process. The main question is to what extent does the workload
Tóth, B.; Lillo, F.; Farmer, J. D.
2010-11-01
We introduce an algorithm for the segmentation of a class of regime switching processes. The segmentation algorithm is a non parametric statistical method able to identify the regimes (patches) of a time series. The process is composed of consecutive patches of variable length. In each patch the process is described by a stationary compound Poisson process, i.e. a Poisson process where each count is associated with a fluctuating signal. The parameters of the process are different in each patch and therefore the time series is non-stationary. Our method is a generalization of the algorithm introduced by Bernaola-Galván, et al. [Phys. Rev. Lett. 87, 168105 (2001)]. We show that the new algorithm outperforms the original one for regime switching models of compound Poisson processes. As an application we use the algorithm to segment the time series of the inventory of market members of the London Stock Exchange and we observe that our method finds almost three times more patches than the original one.
Random attractors for stochastic lattice reversible Gray-Scott systems with additive noise
Directory of Open Access Journals (Sweden)
Hongyan Li
2015-10-01
Full Text Available In this article, we prove the existence of a random attractor of the stochastic three-component reversible Gray-Scott system on infinite lattice with additive noise. We use a transformation of addition involved with Ornstein-Uhlenbeck process, for proving the pullback absorbing property and the pullback asymptotic compactness of the reaction diffusion system with cubic nonlinearity.
Afrika Statistika ISSN 2316-090X On drift estimation for non-ergodic ...
African Journals Online (AJOL)
Key words: Drift estimation; Discrete observations; Ornstein-Uhlenbeck process; Non- ergodicity. AMS 2010 Mathematics Subject Classification : 60G22; 62M05; 62F12. ∗Corresponding author Khalifa Es-Sebaiy: k.Essebaiy@uca.ma. Djibril Ndiaye : djibykhady@yahoo.fr. 1Supported by ”La commission de l'UEMOA dans le ...
The Morris-Lecar neuron model embeds a leaky integrate-and-fire model
DEFF Research Database (Denmark)
Ditlevsen, Susanne; Greenwood, Priscilla
2013-01-01
We showthat the stochastic Morris–Lecar neuron, in a neighborhood of its stable point, can be approximated by a two-dimensional Ornstein Uhlenbeck (OU) modulation of a constant circular motion. The associated radial OU process is an example of a leaky integrate-and-fire (LIF) model prior to firing...
International Nuclear Information System (INIS)
Frank, T.D.
2006-01-01
First-order approximations of time-dependent solutions are determined for stochastic systems perturbed by time-delayed feedback forces. To this end, the theory of delay Fokker-Planck equations is applied in combination with Bayes' theorem. Applications to a time-delayed Ornstein-Uhlenbeck process and the geometric Brownian walk of financial physics are discussed
Veestraeten, D.
2015-01-01
The Laplace transforms of the transition probability density and distribution functions for the Ornstein-Uhlenbeck process contain the product of two parabolic cylinder functions, namely Dv(x)Dv(y) and Dv(x)Dv−1(y), respectively. The inverse transforms of these products have as yet not been
Nonstationary quantum mechanics
International Nuclear Information System (INIS)
Todorov, N.S.
1981-01-01
It is shown that the nonstationary Schroedinger equation does not satisfy a well-known adiabatical principle in thermodynamics. A ''renormalization procedure'' based on the possible existence of a time-irreversible basic evolution equation is proposed with the help of which one comes to agreement in a variety of specific cases of an adiabatic inclusion of a perturbing potential. The ideology of the present article rests essentially on the ideology of the preceding articles, in particular article I. (author)
2018-03-10
circuit boards. A computational electromagnetics software package, FEKO [24], is used to model the antenna arrays, and the RMIM [12] is used to...Symposium on Intelligent Signal Processing and Communications Systems, Chengdu, China, 2010. [24] FEKO Suite 6.3, EM Software & Systems- S.A. (Pty) Ltd...including suggestions for reducing the burden, to Department of Defense, Washington Headquarters Services , Directorate for Information Operations and
Nonstationary quantum mechanics. 5. Nonstationary quantum models of scattering
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S [Low Temperature Department of the Institute of Solid State Physics of the Bulgarian Academy of Sciences, Sofia
1981-05-01
Some peculiarities of the results of nonstationary perturbation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed.
Nonstationary quantum mechanics v. nonstationary quantum models of scattering
Energy Technology Data Exchange (ETDEWEB)
Todorov, N S
1981-05-01
Some pecularities of the results of nonstationary pertubation theory in the presence of a degenerate continuous energy spectrum are considered. Their relevance to the ideology of the preceding articles in this series is discussed.
Hazard function theory for nonstationary natural hazards
Read, L.; Vogel, R. M.
2015-12-01
Studies from the natural hazards literature indicate that many natural processes, including wind speeds, landslides, wildfires, precipitation, streamflow and earthquakes, show evidence of nonstationary behavior such as trends in magnitudes through time. Traditional probabilistic analysis of natural hazards based on partial duration series (PDS) generally assumes stationarity in the magnitudes and arrivals of events, i.e. that the probability of exceedance is constant through time. Given evidence of trends and the consequent expected growth in devastating impacts from natural hazards across the world, new methods are needed to characterize their probabilistic behavior. The field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (x) with its failure time series (t), enabling computation of corresponding average return periods and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose PDS magnitudes are assumed to follow the widely applied Poisson-GP model. We derive a 2-parameter Generalized Pareto hazard model and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard event series x, with corresponding failure time series t, should have application to a wide class of natural hazards.
Information retrieval for nonstationary data records
Su, M. Y.
1971-01-01
A review and a critical discussion are made on the existing methods for analysis of nonstationary time series, and a new algorithm for splitting nonstationary time series, is applied to the analysis of sunspot data.
Parametric modelling of nonstationary platform deck motions
Digital Repository Service at National Institute of Oceanography (India)
Mandal, S.
with fast Fourier transform spectra and show good agreement. However, the higher order maximum entropy model can be used for better representation of nonstationary motions. This method also reduces long time series of nonstationary offshore data into a few...
Photorefraction in crystals with nonstationary photovoltaic current
International Nuclear Information System (INIS)
Volk, T.R.; Astaf'ev, S.B.; Razumovskij, N.V.
1995-01-01
Effect of photovoltaic current nonstationary components, conditioned by nonstationary character of photovoltaic centers, on photorefractive properties of LiNbO 3 crystals is considered. Analytic expressions describing nonstationary photovoltaic current effect on kinetics of recording and optical erasure of photorefraction are obtained. A possibility of nonstationary photovoltaic current occurrence in crystals with multilevel charge transfer circuit is considered. Recording light pulse duration effect on photorefraction in LiNbO 3 is discussed. 25 refs., 8 figs
Enhanced tunneling through nonstationary barriers
International Nuclear Information System (INIS)
Palomares-Baez, J. P.; Rodriguez-Lopez, J. L.; Ivlev, B.
2007-01-01
Quantum tunneling through a nonstationary barrier is studied analytically and by a direct numerical solution of Schroedinger equation. Both methods are in agreement and say that the main features of the phenomenon can be described in terms of classical trajectories which are solutions of Newton's equation in complex time. The probability of tunneling is governed by analytical properties of a time-dependent perturbation and the classical trajectory in the plane of complex time. Some preliminary numerical calculations of Euclidean resonance (an easy penetration through a classical nonstationary barrier due to an underbarrier interference) are presented
Damping Identification of Bridges Under Nonstationary Ambient Vibration
Directory of Open Access Journals (Sweden)
Sunjoong Kim
2017-12-01
Full Text Available This research focuses on identifying the damping ratio of bridges using nonstationary ambient vibration data. The damping ratios of bridges in service have generally been identified using operational modal analysis (OMA based on a stationary white noise assumption for input signals. However, most bridges are generally subjected to nonstationary excitations while in service, and this violation of the basic assumption can lead to uncertainties in damping identification. To deal with nonstationarity, an amplitude-modulating function was calculated from measured responses to eliminate global trends caused by nonstationary input. A natural excitation technique (NExT-eigensystem realization algorithm (ERA was applied to estimate the damping ratio for a stationarized process. To improve the accuracy of OMA-based damping estimates, a comparative analysis was performed between an extracted stationary process and nonstationary data to assess the effect of eliminating nonstationarity. The mean value and standard deviation of the damping ratio for the first vertical mode decreased after signal stationarization. Keywords: Damping, Operational modal analysis, Traffic-induced vibration, Nonstationary, Signal stationarization, Amplitude-modulating, Bridge, Cable-stayed, Suspension
Correlation, Regression, and Cointegration of Nonstationary Economic Time Series
DEFF Research Database (Denmark)
Johansen, Søren
), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coefficients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coefficients do not converge to the relevant population...... values, due to the trending nature of the data. We conclude by giving a simple cointegration analysis of two interests. The analysis illustrates that much more insight can be gained about the dynamic behavior of the nonstationary variables then simply by calculating a correlation coefficient......Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974...
Correlation, regression, and cointegration of nonstationary economic time series
DEFF Research Database (Denmark)
Johansen, Søren
Yule (1926) introduced the concept of spurious or nonsense correlation, and showed by simulation that for some nonstationary processes, that the empirical correlations seem not to converge in probability even if the processes were independent. This was later discussed by Granger and Newbold (1974......), and Phillips (1986) found the limit distributions. We propose to distinguish between empirical and population correlation coeffients and show in a bivariate autoregressive model for nonstationary variables that the empirical correlation and regression coe¢ cients do not converge to the relevant population...
Hazard function theory for nonstationary natural hazards
Read, Laura K.; Vogel, Richard M.
2016-04-01
Impact from natural hazards is a shared global problem that causes tremendous loss of life and property, economic cost, and damage to the environment. Increasingly, many natural processes show evidence of nonstationary behavior including wind speeds, landslides, wildfires, precipitation, streamflow, sea levels, and earthquakes. Traditional probabilistic analysis of natural hazards based on peaks over threshold (POT) generally assumes stationarity in the magnitudes and arrivals of events, i.e., that the probability of exceedance of some critical event is constant through time. Given increasing evidence of trends in natural hazards, new methods are needed to characterize their probabilistic behavior. The well-developed field of hazard function analysis (HFA) is ideally suited to this problem because its primary goal is to describe changes in the exceedance probability of an event over time. HFA is widely used in medicine, manufacturing, actuarial statistics, reliability engineering, economics, and elsewhere. HFA provides a rich theory to relate the natural hazard event series (X) with its failure time series (T), enabling computation of corresponding average return periods, risk, and reliabilities associated with nonstationary event series. This work investigates the suitability of HFA to characterize nonstationary natural hazards whose POT magnitudes are assumed to follow the widely applied generalized Pareto model. We derive the hazard function for this case and demonstrate how metrics such as reliability and average return period are impacted by nonstationarity and discuss the implications for planning and design. Our theoretical analysis linking hazard random variable X with corresponding failure time series T should have application to a wide class of natural hazards with opportunities for future extensions.
Mallak, Saed
1996-01-01
Ankara : Department of Mathematics and Institute of Engineering and Sciences of Bilkent University, 1996. Thesis (Master's) -- Bilkent University, 1996. Includes bibliographical references leaves leaf 29 In thi.s work, we studierl the Ergodicilv of Non-Stationary .Markov chains. We gave several e.xainples with different cases. We proved that given a sec[uence of Markov chains such that the limit of this sec|uence is an Ergodic Markov chain, then the limit of the combination ...
Nonstationary Narrow-Band Response and First-Passage Probability
DEFF Research Database (Denmark)
Krenk, Steen
1979-01-01
The notion of a nonstationary narrow-band stochastic process is introduced without reference to a frequency spectrum, and the joint distribution function of two consecutive maxima is approximated by use of an envelope. Based on these definitions the first passage problem is treated as a Markov po...
Cointegration and Econometric Analysis of Non-Stationary Data in ...
African Journals Online (AJOL)
This is in conformity with the philosophy underlying the cointegration theory. Therefore, ignoring cointegration in non-stationary time series variables could lead to misspecification of the underlying process in the determination of corporate income tax in Nigeria. Thus, the study conclude that cointegration is greatly enhanced ...
Maximum-entropy description of animal movement.
Fleming, Chris H; Subaşı, Yiğit; Calabrese, Justin M
2015-03-01
We introduce a class of maximum-entropy states that naturally includes within it all of the major continuous-time stochastic processes that have been applied to animal movement, including Brownian motion, Ornstein-Uhlenbeck motion, integrated Ornstein-Uhlenbeck motion, a recently discovered hybrid of the previous models, and a new model that describes central-place foraging. We are also able to predict a further hierarchy of new models that will emerge as data quality improves to better resolve the underlying continuity of animal movement. Finally, we also show that Langevin equations must obey a fluctuation-dissipation theorem to generate processes that fall from this class of maximum-entropy distributions when the constraints are purely kinematic.
The multivariate supOU stochastic volatility model
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Stelzer, Robert
Using positive semidefinite supOU (superposition of Ornstein-Uhlenbeck type) processes to describe the volatility, we introduce a multivariate stochastic volatility model for financial data which is capable of modelling long range dependence effects. The finiteness of moments and the second order...... structure of the volatility, the log returns, as well as their "squares" are discussed in detail. Moreover, we give several examples in which long memory effects occur and study how the model as well as the simple Ornstein-Uhlenbeck type stochastic volatility model behave under linear transformations....... In particular, the models are shown to be preserved under invertible linear transformations. Finally, we discuss how (sup)OU stochastic volatility models can be combined with a factor modelling approach....
Optimal consumption problem in the Vasicek model
Directory of Open Access Journals (Sweden)
Jakub Trybuła
2015-01-01
Full Text Available We consider the problem of an optimal consumption strategy on the infinite time horizon based on the hyperbolic absolute risk aversion utility when the interest rate is an Ornstein-Uhlenbeck process. Using the method of subsolution and supersolution we obtain the existence of solutions of the dynamic programming equation. We illustrate the paper with a numerical example of the optimal consumption strategy and the value function.
Nonstationary Hydrological Frequency Analysis: Theoretical Methods and Application Challenges
Xiong, L.
2014-12-01
Because of its great implications in the design and operation of hydraulic structures under changing environments (either climate change or anthropogenic changes), nonstationary hydrological frequency analysis has become so important and essential. Two important achievements have been made in methods. Without adhering to the consistency assumption in the traditional hydrological frequency analysis, the time-varying probability distribution of any hydrological variable can be established by linking the distribution parameters to some covariates such as time or physical variables with the help of some powerful tools like the Generalized Additive Model of Location, Scale and Shape (GAMLSS). With the help of copulas, the multivariate nonstationary hydrological frequency analysis has also become feasible. However, applications of the nonstationary hydrological frequency formula to the design and operation of hydraulic structures for coping with the impacts of changing environments in practice is still faced with many challenges. First, the nonstationary hydrological frequency formulae with time as covariate could only be extrapolated for a very short time period beyond the latest observation time, because such kind of formulae is not physically constrained and the extrapolated outcomes could be unrealistic. There are two physically reasonable methods that can be used for changing environments, one is to directly link the quantiles or the distribution parameters to some measureable physical factors, and the other is to use the derived probability distributions based on hydrological processes. However, both methods are with a certain degree of uncertainty. For the design and operation of hydraulic structures under changing environments, it is recommended that design results of both stationary and nonstationary methods be presented together and compared with each other, to help us understand the potential risks of each method.
Nonstationary oscillations in gyrotrons revisited
International Nuclear Information System (INIS)
Dumbrajs, O.; Kalis, H.
2015-01-01
Development of gyrotrons requires careful understanding of different regimes of gyrotron oscillations. It is known that in the planes of the generalized gyrotron variables: cyclotron resonance mismatch and dimensionless current or cyclotron resonance mismatch and dimensionless interaction length complicated alternating sequences of regions of stationary, periodic, automodulation, and chaotic oscillations exist. In the past, these regions were investigated on the supposition that the transit time of electrons through the interaction space is much shorter than the cavity decay time. This assumption is valid for short and/or high diffraction quality resonators. However, in the case of long and/or low diffraction quality resonators, which are often utilized, this assumption is no longer valid. In such a case, a different mathematical formalism has to be used for studying nonstationary oscillations. One example of such a formalism is described in the present paper
Learning in Non-Stationary Environments Methods and Applications
Lughofer, Edwin
2012-01-01
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...
Loss energy states of nonstationary quantum systems
International Nuclear Information System (INIS)
Dodonov, V.V.; Man'ko, V.I.
1978-01-01
The concept of loss energy states is introduced. The loss energy states of the quantum harmonic damping oscillator are considered in detail. The method of constructing the loss energy states for general multidimensional quadratic nonstationary quantum systems is briefly discussed
Splines employment for inverse problem of nonstationary thermal conduction
International Nuclear Information System (INIS)
Nikonov, S.P.; Spolitak, S.I.
1985-01-01
An analytical solution has been obtained for an inverse problem of nonstationary thermal conduction which is faced in nonstationary heat transfer data processing when the rewetting in channels with uniform annular fuel element imitators is investigated. In solving the problem both boundary conditions and power density within the imitator are regularized via cubic splines constructed with the use of Reinsch algorithm. The solution can be applied for calculation of temperature distribution in the imitator and the heat flux in two-dimensional approximation (r-z geometry) under the condition that the rewetting front velocity is known, and in one-dimensional r-approximation in cases with negligible axial transport or when there is a lack of data about the temperature disturbance source velocity along the channel
Non-stationary condition monitoring through event alignment
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan
2004-01-01
We present an event alignment framework which enables change detection in non-stationary signals. change detection. Classical condition monitoring frameworks have been restrained to laboratory settings with stationary operating conditions, which are not resembling real world operation....... In this paper we apply the technique for non-stationary condition monitoring of large diesel engines based on acoustical emission sensor signals. The performance of the event alignment is analyzed in an unsupervised probabilistic detection framework based on outlier detection with either Principal Component...... Analysis or Gaussian Processes modeling. We are especially interested in the true performance of the condition monitoring performance with mixed aligned and unaligned data, e.g. detection of fault condition of unaligned examples versus false alarms of aligned normal condition data. Further, we expect...
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaël
2016-03-03
Max-stable processes are natural models for spatial extremes because they provide suitable asymptotic approximations to the distribution of maxima of random fields. In the recent past, several parametric families of stationary max-stable models have been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference is performed using pairwise likelihoods, and its performance is assessed by an extensive simulation study based on a non-stationary locally isotropic extremal t model. Evidence that unknown parameters are well estimated is provided, and estimation of spatial return level curves is discussed. The methodology is demonstrated with temperature maxima recorded over a complex topography. Models are shown to satisfactorily capture extremal dependence.
Thin viscoelastic disc subjected to radial non-stationary loading
Directory of Open Access Journals (Sweden)
Adámek V.
2010-07-01
Full Text Available The investigation of non-stationary wave phenomena in isotropic viscoelastic solids using analytical approaches is the aim of this paper. Concretely, the problem of a thin homogeneous disc subjected to radial pressure load nonzero on the part of its rim is solved. The external excitation is described by the Heaviside function in time, so the nonstationary state of stress is induced in the disc. Dissipative material behaviour of solid studied is represented by the discrete material model of standard linear viscoelastic solid in the Zener configuration. After the derivation of motion equations final form, the method of integral transforms in combination with the Fourier method is used for finding the problem solution. The solving process results in the derivation of integral transforms of radial and circumferential displacement components. Finally, the type of derived functions singularities and possible methods for their inverse Laplace transform are mentioned.
Stationary and nonstationary properties of evolving networks with preferential linkage
International Nuclear Information System (INIS)
Jezewski, W.
2002-01-01
Networks evolving by preferential attachment of both external and internal links are investigated. The rate of adding an external link is assumed to depend linearly on the degree of a preexisting node to which a new node is connected. The process of creating an internal link, between a pair of existing vertices, is assumed to be controlled entirely by the vertex that has more links than the other vertex in the pair, and the rate of creation of such a link is assumed to be, in general, nonlinear in the degree of the more strongly connected vertex. It is shown that degree distributions of networks evolving only by creating internal links display for large degrees a nonstationary power-law decay with a time-dependent scaling exponent. Nonstationary power-law behaviors are numerically shown to persist even when the number of nodes is not fixed and both external and internal connections are introduced, provided that the rate of preferential attachment of internal connections is nonlinear. It is argued that nonstationary effects are not unlikely in real networks, although these effects may not be apparent, especially in networks with a slowly varying mean degree
Schillinger, Dominik
2013-07-01
The method of separation can be used as a non-parametric estimation technique, especially suitable for evolutionary spectral density functions of uniformly modulated and strongly narrow-band stochastic processes. The paper at hand provides a consistent derivation of method of separation based spectrum estimation for the general multi-variate and multi-dimensional case. The validity of the method is demonstrated by benchmark tests with uniformly modulated spectra, for which convergence to the analytical solution is demonstrated. The key advantage of the method of separation is the minimization of spectral dispersion due to optimum time- or space-frequency localization. This is illustrated by the calibration of multi-dimensional and multi-variate geometric imperfection models from strongly narrow-band measurements in I-beams and cylindrical shells. Finally, the application of the method of separation based estimates for the stochastic buckling analysis of the example structures is briefly discussed. © 2013 Elsevier Ltd.
Sparse Bayesian Learning for Nonstationary Data Sources
Fujimaki, Ryohei; Yairi, Takehisa; Machida, Kazuo
This paper proposes an online Sparse Bayesian Learning (SBL) algorithm for modeling nonstationary data sources. Although most learning algorithms implicitly assume that a data source does not change over time (stationary), one in the real world usually does due to such various factors as dynamically changing environments, device degradation, sudden failures, etc (nonstationary). The proposed algorithm can be made useable for stationary online SBL by setting time decay parameters to zero, and as such it can be interpreted as a single unified framework for online SBL for use with stationary and nonstationary data sources. Tests both on four types of benchmark problems and on actual stock price data have shown it to perform well.
Cultural evolution as a nonstationary stochastic process
DEFF Research Database (Denmark)
Nicholson, Arwen; Sibani, Paolo
2016-01-01
We present an individual based model of cultural evolution, where interacting agents are coded by binary strings standing for strategies for action, blueprints for products or attitudes and beliefs. The model is patterned on an established model of biological evolution, the Tangled Nature Model...... (TNM), where a “tangle” of interactions between agents determines their reproductive success. In addition, our agents also have the ability to copy part of each other's strategy, a feature inspired by the Axelrod model of cultural diversity. Unlike the latter, but similarly to the TNM, the model...
Non-stationary pre-envelope covariances of non-classically damped systems
Muscolino, G.
1991-08-01
A new formulation is given to evaluate the stationary and non-stationary response of linear non-classically damped systems subjected to multi-correlated non-separable Gaussian input processes. This formulation is based on a new and more suitable definition of the impulse response function matrix for such systems. It is shown that, when using this definition, the stochastic response of non-classically damped systems involves the evaluation of quantities similar to those of classically damped ones. Furthermore, considerations about non-stationary cross-covariances, spectral moments and pre-envelope cross-covariances are presented for a monocorrelated input process.
Radiation of light impurities in a nonstationary plasma
International Nuclear Information System (INIS)
Abramov, V.A.; Krotova, G.I.
1984-01-01
In the framework of a nonstationary coronal model with account for latest data on elementary process cross sections calculations of oxygen radiation power are performed. It is shown that taking into account electron temperature nonstationarity characteristic of the initial stage in nowadays tokamaks, line emission power in the principal maximum region (Tsub(e) approximately 40 eV) changes but slightly, whereas the radiation power in the second maximum (Tsub(e) approximately 100 eV increases approximately 20 times as compared with stationary values
Staffing a call center with uncertain non-stationary arrival rate and flexibility
Liao, S.; van Delft, C.; Jouini, O.; Koole, G.M.
2012-01-01
We consider a multi-period staffing problem in a single-shift call center. The call center handles inbound calls, as well as some alternative back-office jobs. The call arrival process is assumed to follow a doubly non-stationary stochastic process with a random mean arrival rate. The inbound calls
Nonstationary stochastic charge fluctuations of a dust particle in plasmas.
Shotorban, B
2011-06-01
Stochastic charge fluctuations of a dust particle that are due to discreteness of electrons and ions in plasmas can be described by a one-step process master equation [T. Matsoukas and M. Russell, J. Appl. Phys. 77, 4285 (1995)] with no exact solution. In the present work, using the system size expansion method of Van Kampen along with the linear noise approximation, a Fokker-Planck equation with an exact Gaussian solution is developed by expanding the master equation. The Gaussian solution has time-dependent mean and variance governed by two ordinary differential equations modeling the nonstationary process of dust particle charging. The model is tested via the comparison of its results to the results obtained by solving the master equation numerically. The electron and ion currents are calculated through the orbital motion limited theory. At various times of the nonstationary process of charging, the model results are in a very good agreement with the master equation results. The deviation is more significant when the standard deviation of the charge is comparable to the mean charge in magnitude.
Testing Local Independence between Two Point Processes
DEFF Research Database (Denmark)
Allard, Denis; Brix, Anders; Chadæuf, Joël
2001-01-01
Independence test, Inhomogeneous point processes, Local test, Monte Carlo, Nonstationary, Rotations, Spatial pattern, Tiger bush......Independence test, Inhomogeneous point processes, Local test, Monte Carlo, Nonstationary, Rotations, Spatial pattern, Tiger bush...
Directory of Open Access Journals (Sweden)
Rehan Balqis M.
2016-01-01
Full Text Available Current practice in flood frequency analysis assumes that the stochastic properties of extreme floods follow that of stationary conditions. As human intervention and anthropogenic climate change influences in hydrometeorological variables are becoming evident in some places, there have been suggestions that nonstationary statistics would be better to represent the stochastic properties of the extreme floods. The probabilistic estimation of non-stationary models, however, is surrounded with uncertainty related to scarcity of observations and modelling complexities hence the difficulty to project the future condition. In the face of uncertain future and the subjectivity of model choices, this study attempts to demonstrate the practical implications of applying a nonstationary model and compares it with a stationary model in flood risk assessment. A fully integrated framework to simulate decision makers’ behaviour in flood frequency analysis is thereby developed. The framework is applied to hypothetical flood risk management decisions and the outcomes are compared with those of known underlying future conditions. Uncertainty of the economic performance of the risk-based decisions is assessed through Monte Carlo simulations. Sensitivity of the results is also tested by varying the possible magnitude of future changes. The application provides quantitative and qualitative comparative results that satisfy a preliminary analysis of whether the nonstationary model complexity should be applied to improve the economic performance of decisions. Results obtained from the case study shows that the relative differences of competing models for all considered possible future changes are small, suggesting that stationary assumptions are preferred to a shift to nonstationary statistics for practical application of flood risk management. Nevertheless, nonstationary assumption should also be considered during a planning stage in addition to stationary assumption
Nonstationary interference and scattering from random media
International Nuclear Information System (INIS)
Nazikian, R.
1991-12-01
For the small angle scattering of coherent plane waves from inhomogeneous random media, the three dimensional mean square distribution of random fluctuations may be recovered from the interferometric detection of the nonstationary modulational structure of the scattered field. Modulational properties of coherent waves scattered from random media are related to nonlocal correlations in the double sideband structure of the Fourier transform of the scattering potential. Such correlations may be expressed in terms of a suitability generalized spectral coherence function for analytic fields
Likelihood inference for a nonstationary fractional autoregressive model
DEFF Research Database (Denmark)
Johansen, Søren; Ørregård Nielsen, Morten
2010-01-01
This paper discusses model-based inference in an autoregressive model for fractional processes which allows the process to be fractional of order d or d-b. Fractional differencing involves infinitely many past values and because we are interested in nonstationary processes we model the data X1......,...,X_{T} given the initial values X_{-n}, n=0,1,..., as is usually done. The initial values are not modeled but assumed to be bounded. This represents a considerable generalization relative to all previous work where it is assumed that initial values are zero. For the statistical analysis we assume...... the conditional Gaussian likelihood and for the probability analysis we also condition on initial values but assume that the errors in the autoregressive model are i.i.d. with suitable moment conditions. We analyze the conditional likelihood and its derivatives as stochastic processes in the parameters, including...
EDITORIAL: CAMOP: Quantum Non-Stationary Systems CAMOP: Quantum Non-Stationary Systems
Dodonov, Victor V.; Man'ko, Margarita A.
2010-09-01
Although time-dependent quantum systems have been studied since the very beginning of quantum mechanics, they continue to attract the attention of many researchers, and almost every decade new important discoveries or new fields of application are made. Among the impressive results or by-products of these studies, one should note the discovery of the path integral method in the 1940s, coherent and squeezed states in the 1960-70s, quantum tunneling in Josephson contacts and SQUIDs in the 1960s, the theory of time-dependent quantum invariants in the 1960-70s, different forms of quantum master equations in the 1960-70s, the Zeno effect in the 1970s, the concept of geometric phase in the 1980s, decoherence of macroscopic superpositions in the 1980s, quantum non-demolition measurements in the 1980s, dynamics of particles in quantum traps and cavity QED in the 1980-90s, and time-dependent processes in mesoscopic quantum devices in the 1990s. All these topics continue to be the subject of many publications. Now we are witnessing a new wave of interest in quantum non-stationary systems in different areas, from cosmology (the very first moments of the Universe) and quantum field theory (particle pair creation in ultra-strong fields) to elementary particle physics (neutrino oscillations). A rapid increase in the number of theoretical and experimental works on time-dependent phenomena is also observed in quantum optics, quantum information theory and condensed matter physics. Time-dependent tunneling and time-dependent transport in nano-structures are examples of such phenomena. Another emerging direction of study, stimulated by impressive progress in experimental techniques, is related to attempts to observe the quantum behavior of macroscopic objects, such as mirrors interacting with quantum fields in nano-resonators. Quantum effects manifest themselves in the dynamics of nano-electromechanical systems; they are dominant in the quite new and very promising field of circuit
A Nonstationary Markov Model Detects Directional Evolution in Hymenopteran Morphology.
Klopfstein, Seraina; Vilhelmsen, Lars; Ronquist, Fredrik
2015-11-01
Directional evolution has played an important role in shaping the morphological, ecological, and molecular diversity of life. However, standard substitution models assume stationarity of the evolutionary process over the time scale examined, thus impeding the study of directionality. Here we explore a simple, nonstationary model of evolution for discrete data, which assumes that the state frequencies at the root differ from the equilibrium frequencies of the homogeneous evolutionary process along the rest of the tree (i.e., the process is nonstationary, nonreversible, but homogeneous). Within this framework, we develop a Bayesian approach for testing directional versus stationary evolution using a reversible-jump algorithm. Simulations show that when only data from extant taxa are available, the success in inferring directionality is strongly dependent on the evolutionary rate, the shape of the tree, the relative branch lengths, and the number of taxa. Given suitable evolutionary rates (0.1-0.5 expected substitutions between root and tips), accounting for directionality improves tree inference and often allows correct rooting of the tree without the use of an outgroup. As an empirical test, we apply our method to study directional evolution in hymenopteran morphology. We focus on three character systems: wing veins, muscles, and sclerites. We find strong support for a trend toward loss of wing veins and muscles, while stationarity cannot be ruled out for sclerites. Adding fossil and time information in a total-evidence dating approach, we show that accounting for directionality results in more precise estimates not only of the ancestral state at the root of the tree, but also of the divergence times. Our model relaxes the assumption of stationarity and reversibility by adding a minimum of additional parameters, and is thus well suited to studying the nature of the evolutionary process in data sets of limited size, such as morphology and ecology. © The Author
Non-stationary compositions of Anosov diffeomorphisms
International Nuclear Information System (INIS)
Stenlund, Mikko
2011-01-01
Motivated by non-equilibrium phenomena in nature, we study dynamical systems whose time-evolution is determined by non-stationary compositions of chaotic maps. The constituent maps are topologically transitive Anosov diffeomorphisms on a two-dimensional compact Riemannian manifold, which are allowed to change with time—slowly, but in a rather arbitrary fashion. In particular, such systems admit no invariant measure. By constructing a coupling, we prove that any two sufficiently regular distributions of the initial state converge exponentially with time. Thus, a system of this kind loses memory of its statistical history rapidly
Fermat principle for a nonstationary medium.
Voronovich, A G; Godin, O A
2003-07-25
One possible formulation of a variational principle of the Fermat type for systems with time-dependent parameters is suggested. In a stationary case, it reduces to the Mopertui-Lagrange least-action principle. A class of Hamiltonians (dispersion relations) is indicated, for which the variational principle reduces to the Fermat principle in a general nonstationary case. Hamiltonians that are homogeneous functions of momenta are in this category. For the important case of nondispersive waves (corresponding to Hamiltonians being homogeneous function of momenta order 1) the Fermat principle fully determines the geometry of the rays. Equations relating the variation of signal frequency with the rate of change of propagation time are established.
Huang, Weilin; Wang, Runqiu; Chen, Yangkang
2018-05-01
Microseismic signal is typically weak compared with the strong background noise. In order to effectively detect the weak signal in microseismic data, we propose a mathematical morphology based approach. We decompose the initial data into several morphological multiscale components. For detection of weak signal, a non-stationary weighting operator is proposed and introduced into the process of reconstruction of data by morphological multiscale components. The non-stationary weighting operator can be obtained by solving an inversion problem. The regularized non-stationary method can be understood as a non-stationary matching filtering method, where the matching filter has the same size as the data to be filtered. In this paper, we provide detailed algorithmic descriptions and analysis. The detailed algorithm framework, parameter selection and computational issue for the regularized non-stationary morphological reconstruction (RNMR) method are presented. We validate the presented method through a comprehensive analysis through different data examples. We first test the proposed technique using a synthetic data set. Then the proposed technique is applied to a field project, where the signals induced from hydraulic fracturing are recorded by 12 three-component geophones in a monitoring well. The result demonstrates that the RNMR can improve the detectability of the weak microseismic signals. Using the processed data, the short-term-average over long-term average picking algorithm and Geiger's method are applied to obtain new locations of microseismic events. In addition, we show that the proposed RNMR method can be used not only in microseismic data but also in reflection seismic data to detect the weak signal. We also discussed the extension of RNMR from 1-D to 2-D or a higher dimensional version.
A simple nonstationary-volatility robust panel unit root test
Demetrescu, Matei; Hanck, Christoph
2012-01-01
We propose an IV panel unit root test robust to nonstationary error volatility. Its finite-sample performance is convincing even for many units and strong cross-correlation. An application to GDP prices illustrates the inferential impact of nonstationary volatility. (C) 2012 Elsevier B.V. All rights
Analysis of stress and deformation in non-stationary creep
International Nuclear Information System (INIS)
Feijoo, R.A.; Taroco, E.; Guerreiro, J.N.C.
1980-12-01
A variational method and its algorithm are presented; they permit the analysis of stress and deformation in non-stationary creep. This algorithm is applied to an infinite cylinder submitted to an internal pressure. The solution obtained is compared with the solution of non-stationary creep problems [pt
Martingales, nonstationary increments, and the efficient market hypothesis
McCauley, Joseph L.; Bassler, Kevin E.; Gunaratne, Gemunu H.
2008-06-01
We discuss the deep connection between nonstationary increments, martingales, and the efficient market hypothesis for stochastic processes x(t) with arbitrary diffusion coefficients D(x,t). We explain why a test for a martingale is generally a test for uncorrelated increments. We explain why martingales look Markovian at the level of both simple averages and 2-point correlations. But while a Markovian market has no memory to exploit and cannot be beaten systematically, a martingale admits memory that might be exploitable in higher order correlations. We also use the analysis of this paper to correct a misstatement of the ‘fair game’ condition in terms of serial correlations in Fama’s paper on the EMH. We emphasize that the use of the log increment as a variable in data analysis generates spurious fat tails and spurious Hurst exponents.
Simulation of nonstationary phenomena in atmospheric-pressure glow discharge
Korolev, Yu. D.; Frants, O. B.; Nekhoroshev, V. O.; Suslov, A. I.; Kas'yanov, V. S.; Shemyakin, I. A.; Bolotov, A. V.
2016-06-01
Nonstationary processes in atmospheric-pressure glow discharge manifest themselves in spontaneous transitions from the normal glow discharge into a spark. In the experiments, both so-called completed transitions in which a highly conductive constricted channel arises and incomplete transitions accompanied by the formation of a diffuse channel are observed. A model of the positive column of a discharge in air is elaborated that allows one to interpret specific features of the discharge both in the stationary stage and during its transition into a spark and makes it possible to calculate the characteristic oscillatory current waveforms for completed transitions into a spark and aperiodic ones for incomplete transitions. The calculated parameters of the positive column in the glow discharge mode agree well with experiment. Data on the densities of the most abundant species generated in the discharge (such as atomic oxygen, metastable nitrogen molecules, ozone, nitrogen oxides, and negative oxygen ions) are presented.
Simulation of nonstationary phenomena in atmospheric-pressure glow discharge
International Nuclear Information System (INIS)
Korolev, Yu. D.; Frants, O. B.; Nekhoroshev, V. O.; Suslov, A. I.; Kas’yanov, V. S.; Shemyakin, I. A.; Bolotov, A. V.
2016-01-01
Nonstationary processes in atmospheric-pressure glow discharge manifest themselves in spontaneous transitions from the normal glow discharge into a spark. In the experiments, both so-called completed transitions in which a highly conductive constricted channel arises and incomplete transitions accompanied by the formation of a diffuse channel are observed. A model of the positive column of a discharge in air is elaborated that allows one to interpret specific features of the discharge both in the stationary stage and during its transition into a spark and makes it possible to calculate the characteristic oscillatory current waveforms for completed transitions into a spark and aperiodic ones for incomplete transitions. The calculated parameters of the positive column in the glow discharge mode agree well with experiment. Data on the densities of the most abundant species generated in the discharge (such as atomic oxygen, metastable nitrogen molecules, ozone, nitrogen oxides, and negative oxygen ions) are presented.
Amplitudes of solar p modes: Modelling of the eddy time-correlation function
Energy Technology Data Exchange (ETDEWEB)
Belkacem, K [Institut d' Astrophysique et de Geophysique, Universite de Liege, Allee du 6 Aout 17-B 4000 Liege (Belgium); Samadi, R; Goupil, M J, E-mail: Kevin.Belkacem@ulg.ac.BE [LESIA, UMR8109, Universite Pierre et Marie Curie, Universite Denis Diderot, Obs. de Paris, 92195 Meudon Cedex (France)
2011-01-01
Modelling amplitudes of stochastically excited oscillations in stars is a powerful tool for understanding the properties of the convective zones. For instance, it gives us information on the way turbulent eddies are temporally correlated in a very large Reynolds number regime. We discuss the way the time correlation between eddies is modelled and we present recent theoretical developments as well as observational results. Eventually, we discuss the physical underlying meaning of the results by introducing the Ornstein-Uhlenbeck process, which is a sub-class of a Gaussian Markov process.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation
Energy Technology Data Exchange (ETDEWEB)
Huang, Yong, E-mail: hy@njust.edu.cn, E-mail: taogang@njust.edu.cn; Tao, Gang, E-mail: hy@njust.edu.cn, E-mail: taogang@njust.edu.cn [School of Energy and Power Engineering, Nanjing University of Science and Technology, 200 XiaoLingwei Street, Nanjing 210094 (China)
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.
A feedback control strategy for the airfoil system under non-Gaussian colored noise excitation.
Huang, Yong; Tao, Gang
2014-09-01
The stability of a binary airfoil with feedback control under stochastic disturbances, a non-Gaussian colored noise, is studied in this paper. First, based on some approximated theories and methods the non-Gaussian colored noise is simplified to an Ornstein-Uhlenbeck process. Furthermore, via the stochastic averaging method and the logarithmic polar transformation, one dimensional diffusion process can be obtained. At last by applying the boundary conditions, the largest Lyapunov exponent which can determine the almost-sure stability of the system and the effective region of control parameters is calculated.
THE VOLATILITY OF TEMPERATURE AND PRICING OF WEATHER DERIVATIVES
Benth, Fred Espen; Saltyte-Benth, Jurate
2005-01-01
We propose an Ornstein-Uhlenbeck process with seasonal volatility to model the time dynamics of daily average temperatures. The model is fitted to almost 43 years of daily observations recorded in Stockholm, one of the European cities for which there is a trade in weather futures and options on the Chicago Mercantile Exchange (CME). Explicit pricing dynamics for futures contracts written on the number of heating/cooling degree-days (so-called HDD/CDD-futures) and the cumulative average daily ...
Only through perturbation can relaxation times be estimated
DEFF Research Database (Denmark)
Ditlevsen, Susanne; Lansky, Petr
2012-01-01
Estimation of model parameters is as important as model building, but is often neglected in model studies. Here we show that despite the existence of well known results on parameter estimation in a simple homogenous Ornstein-Uhlenbeck process, in most practical situations the methods suffer greatly...... on computer experiments based on applications in neuroscience and pharmacokinetics, which show a striking improvement of the quality of estimation. The results are important for judicious designs of experiments to obtain maximal information from each data point, especially when samples are expensive...
Fractional Number Operator and Associated Fractional Diffusion Equations
Rguigui, Hafedh
2018-03-01
In this paper, we study the fractional number operator as an analog of the finite-dimensional fractional Laplacian. An important relation with the Ornstein-Uhlenbeck process is given. Using a semigroup approach, the solution of the Cauchy problem associated to the fractional number operator is presented. By means of the Mittag-Leffler function and the Laplace transform, we give the solution of the Caputo time fractional diffusion equation and Riemann-Liouville time fractional diffusion equation in infinite dimensions associated to the fractional number operator.
Lyapunov exponent of the random frequency oscillator: cumulant expansion approach
International Nuclear Information System (INIS)
Anteneodo, C; Vallejos, R O
2010-01-01
We consider a one-dimensional harmonic oscillator with a random frequency, focusing on both the standard and the generalized Lyapunov exponents, λ and λ* respectively. We discuss the numerical difficulties that arise in the numerical calculation of λ* in the case of strong intermittency. When the frequency corresponds to a Ornstein-Uhlenbeck process, we compute analytically λ* by using a cumulant expansion including up to the fourth order. Connections with the problem of finding an analytical estimate for the largest Lyapunov exponent of a many-body system with smooth interactions are discussed.
Partitioning uncertainty in streamflow projections under nonstationary model conditions
Chawla, Ila; Mujumdar, P. P.
2018-02-01
Assessing the impacts of Land Use (LU) and climate change on future streamflow projections is necessary for efficient management of water resources. However, model projections are burdened with significant uncertainty arising from various sources. Most of the previous studies have considered climate models and scenarios as major sources of uncertainty, but uncertainties introduced by land use change and hydrologic model assumptions are rarely investigated. In this paper an attempt is made to segregate the contribution from (i) general circulation models (GCMs), (ii) emission scenarios, (iii) land use scenarios, (iv) stationarity assumption of the hydrologic model, and (v) internal variability of the processes, to overall uncertainty in streamflow projections using analysis of variance (ANOVA) approach. Generally, most of the impact assessment studies are carried out with unchanging hydrologic model parameters in future. It is, however, necessary to address the nonstationarity in model parameters with changing land use and climate. In this paper, a regression based methodology is presented to obtain the hydrologic model parameters with changing land use and climate scenarios in future. The Upper Ganga Basin (UGB) in India is used as a case study to demonstrate the methodology. The semi-distributed Variable Infiltration Capacity (VIC) model is set-up over the basin, under nonstationary conditions. Results indicate that model parameters vary with time, thereby invalidating the often-used assumption of model stationarity. The streamflow in UGB under the nonstationary model condition is found to reduce in future. The flows are also found to be sensitive to changes in land use. Segregation results suggest that model stationarity assumption and GCMs along with their interactions with emission scenarios, act as dominant sources of uncertainty. This paper provides a generalized framework for hydrologists to examine stationarity assumption of models before considering them
Non-stationary (13)C-metabolic flux ratio analysis.
Hörl, Manuel; Schnidder, Julian; Sauer, Uwe; Zamboni, Nicola
2013-12-01
(13)C-metabolic flux analysis ((13)C-MFA) has become a key method for metabolic engineering and systems biology. In the most common methodology, fluxes are calculated by global isotopomer balancing and iterative fitting to stationary (13)C-labeling data. This approach requires a closed carbon balance, long-lasting metabolic steady state, and the detection of (13)C-patterns in a large number of metabolites. These restrictions mostly reduced the application of (13)C-MFA to the central carbon metabolism of well-studied model organisms grown in minimal media with a single carbon source. Here we introduce non-stationary (13)C-metabolic flux ratio analysis as a novel method for (13)C-MFA to allow estimating local, relative fluxes from ultra-short (13)C-labeling experiments and without the need for global isotopomer balancing. The approach relies on the acquisition of non-stationary (13)C-labeling data exclusively for metabolites in the proximity of a node of converging fluxes and a local parameter estimation with a system of ordinary differential equations. We developed a generalized workflow that takes into account reaction types and the availability of mass spectrometric data on molecular ions or fragments for data processing, modeling, parameter and error estimation. We demonstrated the approach by analyzing three key nodes of converging fluxes in central metabolism of Bacillus subtilis. We obtained flux estimates that are in agreement with published results obtained from steady state experiments, but reduced the duration of the necessary (13)C-labeling experiment to less than a minute. These results show that our strategy enables to formally estimate relative pathway fluxes on extremely short time scale, neglecting cellular carbon balancing. Hence this approach paves the road to targeted (13)C-MFA in dynamic systems with multiple carbon sources and towards rich media. © 2013 Wiley Periodicals, Inc.
Bučar, Bojan
2007-01-01
The assumption that non-stationary sorption processes associated with wood canbe evaluated by analysis of their transient system response to the disturbance developed is undoubtedly correct. In general it is, in fact, possible to obtain by time analysis of the transient phenomenon - involving the transition into an arbitrary new state of equilibrium - all data required for a credible evaluation of the observed system. Evaluation of moisture movement during drying or moistening requires determ...
Stochastic optimal control of non-stationary response of a single-degree-of-freedom vehicle model
Narayanan, S.; Raju, G. V.
1990-09-01
An active suspension system to control the non-stationary response of a single-degree-of-freedom (sdf) vehicle model with variable velocity traverse over a rough road is investigated. The suspension is optimized with respect to ride comfort and road holding, using stochastic optimal control theory. The ground excitation is modelled as a spatial homogeneous random process, being the output of a linear shaping filter to white noise. The effect of the rolling contact of the tyre is considered by an additional filter in cascade. The non-stationary response with active suspension is compared with that of a passive system.
Teaching geographical hydrology in a non-stationary world
Hendriks, Martin R.; Karssenberg, Derek
2010-05-01
Understanding hydrological processes in a non-stationary world requires knowledge of hydrological processes and their interactions. Also, one needs to understand the (non-linear) relations between the hydrological system and other parts of our Earth system, such as the climate system, the socio-economic system, and the ecosystem. To provide this knowledge and understanding we think that three components are essential when teaching geographical hydrology. First of all, a student needs to acquire a thorough understanding of classical hydrology. For this, knowledge of the basic hydrological equations, such as the energy equation (Bernoulli), flow equation (Darcy), continuity (or water balance) equation is needed. This, however, is not sufficient to make a student fully understand the interactions between hydrological compartments, or between hydrological subsystems and other parts of the Earth system. Therefore, secondly, a student also needs to be knowledgeable of methods by which the different subsystems can be coupled; in general, numerical models are used for this. A major disadvantage of numerical models is their complexity. A solution may be to use simpler models, provided that a student really understands how hydrological processes function in our real, non-stationary world. The challenge for a student then lies in understanding the interactions between the subsystems, and to be able to answer questions such as: what is the effect of a change in vegetation or land use on runoff? Thirdly, knowledge of field hydrology is of utmost importance. For this a student needs to be trained in the field. Fieldwork is very important as a student is confronted in the field with spatial and temporal variability, as well as with real life uncertainties, rather than being lured into believing the world as presented in hydrological textbooks and models, e.g. the world under study is homogeneous, isotropic, or lumped (averaged). Also, students in the field learn to plan and
Advantages of the non-stationary approach: test on eddy current signals
International Nuclear Information System (INIS)
Brunel, P.
1993-12-01
Conventional signal processing is often unsuitable for the interpretation of intrinsically non-stationary signals, such as surveillance or non destructive testing signals. In these cases, ''advanced'' methods are required. This report presents two applications of non-stationary signal processing methods to the complex signals obtained in eddy current non destructive testing of steam generator tubes. The first application consists in segmenting the absolute channel, which can be likened to a piecewise constant signal. The Page-Hinkley cumulative sum algorithm is used, enabling detection of unknown mean amplitude jumps in a piecewise constant signal disturbed by a white noise. Results are comparable to those obtained with the empirical method currently in use. As easy to implement as the latter, the Page-Hinkley algorithm has the added advantage of being well formalized and of identifying whether the jumps in mean are positive or negative. The second application concerns assistance in detecting characteristic fault transients in the differential channels, using the continuous wavelet transform. The useful signal and noise spectra are fairly close, but not strictly identical. With the continuous wavelet transform, these frequency differences can be turned to account. The method was tested on synthetic signals obtained by summing noise and real defect signals. Using the continuous wavelet transform reduces the minimum signal-to-noise ratio by 5 dB for detection of a transient as compared with direct detection on the original signal. Finally, a summary of non-stationary methods using our data is presented. The two investigations described confirm that non-stationary methods may be considered as interesting signal and image analysis tools, as an efficient complement to conventional methods. (author). 24 figs., 13 refs
Gray, A. B.
2017-12-01
Watersheds with sufficient monitoring data have been predominantly found to display nonstationary suspended sediment dynamics, whereby the relationship between suspended sediment concentration and discharge changes over time. Despite the importance of suspended sediment as a keystone of geophysical and biochemical processes, and as a primary mediator of water quality, stationary behavior remains largely assumed in the context of these applications. This study presents an investigation into the time dependent behavior of small mountainous rivers draining the coastal ranges of the western continental US over interannual to interdecadal time scales. Of the 250+ small coastal (drainage area systems. Temporal patterns of non-stationary behavior provided some evidence for spatial coherence, which may be related to synoptic hydro-metrological patterns and regional scale changes in land use patterns. However, the results also highlight the complex, integrative nature of watershed scale fluvial suspended sediment dynamics. This underscores the need for in-depth, forensic approaches for initial processes identification, which require long term, high resolution monitoring efforts in order to adequately inform management. The societal implications of nonstationary sediment dynamics and their controls were further explored through the case of California, USA, where over 150 impairment listings have resulted in more than 50 sediment TMDLs, only 3 of which are flux based - none of which account for non-stationary behavior.
On the non-stationary generalized Langevin equation
Meyer, Hugues; Voigtmann, Thomas; Schilling, Tanja
2017-12-01
In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of such averages is described by the generalized Langevin equation. By contrast, if the dynamics is not stationary, it is not a priori clear which form the equation of motion for an averaged observable has. We employ the formalism of time-dependent projection operator techniques to derive the equation of motion for a non-equilibrium trajectory-averaged observable as well as for its non-stationary auto-correlation function. The equation is similar in structure to the generalized Langevin equation but exhibits a time-dependent memory kernel as well as a fluctuating force that implicitly depends on the initial conditions of the process. We also derive a relation between this memory kernel and the autocorrelation function of the fluctuating force that has a structure similar to a fluctuation-dissipation relation. In addition, we show how the choice of the projection operator allows us to relate the Taylor expansion of the memory kernel to data that are accessible in MD simulations and experiments, thus allowing us to construct the equation of motion. As a numerical example, the procedure is applied to Brownian motion initialized in non-equilibrium conditions and is shown to be consistent with direct measurements from simulations.
Directory of Open Access Journals (Sweden)
X. X. Cheng
2017-01-01
Full Text Available Wind effects on structures obtained by field measurements are often found to be nonstationary, but related researches shared by the wind-engineering community are still limited. In this paper, empirical mode decomposition (EMD is applied to the nonstationary wind pressure time-history samples measured on an actual 167-meter high large cooling tower. It is found that the residue and some intrinsic mode functions (IMFs of low frequencies produced by EMD are responsible for the samples’ nonstationarity. Replacing the residue by the constant mean and subtracting the IMFs of low frequencies can help the nonstationary samples become stationary ones. A further step is taken to compare the loading characteristics extracted from the original nonstationary samples with those extracted from the processed stationary samples. Results indicate that nonstationarity effects on wind loads are notable in most cases. The passive wind tunnel simulation technique based on the assumption of stationarity is also examined, and it is found that the technique is basically conservative for use.
Non-Stationary Internal Tides Observed with Satellite Altimetry
Ray, Richard D.; Zaron, E. D.
2011-01-01
Temporal variability of the internal tide is inferred from a 17-year combined record of Topex/Poseidon and Jason satellite altimeters. A global sampling of along-track sea-surface height wavenumber spectra finds that non-stationary variance is generally 25% or less of the average variance at wavenumbers characteristic of mode-l tidal internal waves. With some exceptions the non-stationary variance does not exceed 0.25 sq cm. The mode-2 signal, where detectable, contains a larger fraction of non-stationary variance, typically 50% or more. Temporal subsetting of the data reveals interannual variability barely significant compared with tidal estimation error from 3-year records. Comparison of summer vs. winter conditions shows only one region of noteworthy seasonal changes, the northern South China Sea. Implications for the anticipated SWOT altimeter mission are briefly discussed.
Faster Simulation Methods for the Non-Stationary Random Vibrations of Non-Linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüoglu, H. U.; Nielsen, Søren R. K.
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Faster Simulation Methods for the Nonstationary Random Vibrations of Non-linear MDOF Systems
DEFF Research Database (Denmark)
Askar, A.; Köylüo, U.; Nielsen, Søren R.K.
1996-01-01
subject to nonstationary Gaussian white noise excitation, as an alternative to conventional direct simulation methods. These alternative simulation procedures rely on an assumption of local Gaussianity during each time step. This assumption is tantamount to various linearizations of the equations....... Such a treatment offers higher rates of convergence, faster speed and higher accuracy. These procedures are compared to the direct Monte Carlo simulation procedure, which uses a fourth order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process...
Sobre uma nova teoria de precificação de opções e outros derivativos
Directory of Open Access Journals (Sweden)
Ailton Cassettari
2001-09-01
Full Text Available Este artigo desenvolve uma nova teoria de precificação de títulos derivativos, implementando-a para a situação particular de opções de compra européias de ações sem dividendos a partir da premissa básica de que o drift do ativo subjacente desempenha papel relevante no processo de precificação, no contexto dos fenômenos de transporte. É feita uma confrontação sistemática com os bem-conhecidos modelos Black-Scholes e Ornstein-Uhlenbeck bivariado que mostra a plausibilidade e efetividade desta abordagem.This paper develops a new theory of derivative securities pricing and implementes it for the specific case of European call options on a hypothetical non-dividend-paying stock. The basic premise is that the drift of the underlying asset plays a very important role in the pricing process, in the context of transport phenomena. A systematic confrontation to well-known Black-Scholes and bivariate trending Ornstein-Uhlenbeck models is also carried out, providing plausibility and effectiveness for this approach.
Non-stationary flow of hydraulic oil in long pipe
Directory of Open Access Journals (Sweden)
Hružík Lumír
2014-03-01
Full Text Available The paper deals with experimental evaluation and numerical simulation of non-stationary flow of hydraulic oil in a long hydraulic line. Non-stationary flow is caused by a quick closing of valves at the beginning and the end of the pipe. Time dependence of pressure is measured by means of pressure sensors at the beginning and the end of the pipe. A mathematical model of a given circuit is created using Matlab SimHydraulics software. The long line is simulated by means of segmented pipe. The simulation is verified by experiment.
Valenza, Gaetano; Faes, Luca; Citi, Luca; Orini, Michele; Barbieri, Riccardo
2018-05-01
Measures of transfer entropy (TE) quantify the direction and strength of coupling between two complex systems. Standard approaches assume stationarity of the observations, and therefore are unable to track time-varying changes in nonlinear information transfer with high temporal resolution. In this study, we aim to define and validate novel instantaneous measures of TE to provide an improved assessment of complex nonstationary cardiorespiratory interactions. We here propose a novel instantaneous point-process TE (ipTE) and validate its assessment as applied to cardiovascular and cardiorespiratory dynamics. In particular, heartbeat and respiratory dynamics are characterized through discrete time series, and modeled with probability density functions predicting the time of the next physiological event as a function of the past history. Likewise, nonstationary interactions between heartbeat and blood pressure dynamics are characterized as well. Furthermore, we propose a new measure of information transfer, the instantaneous point-process information transfer (ipInfTr), which is directly derived from point-process-based definitions of the Kolmogorov-Smirnov distance. Analysis on synthetic data, as well as on experimental data gathered from healthy subjects undergoing postural changes confirms that ipTE, as well as ipInfTr measures are able to dynamically track changes in physiological systems coupling. This novel approach opens new avenues in the study of hidden, transient, nonstationary physiological states involving multivariate autonomic dynamics in cardiovascular health and disease. The proposed method can also be tailored for the study of complex multisystem physiology (e.g., brain-heart or, more in general, brain-body interactions).
Numerical Clifford Analysis for the Non-stationary Schroedinger Equation
International Nuclear Information System (INIS)
Faustino, N.; Vieira, N.
2007-01-01
We construct a discrete fundamental solution for the parabolic Dirac operator which factorizes the non-stationary Schroedinger operator. With such fundamental solution we construct a discrete counterpart for the Teodorescu and Cauchy-Bitsadze operators and the Bergman projectors. We finalize this paper with convergence results regarding the operators and a concrete numerical example
Dynamic Factor Analysis of Nonstationary Multivariate Time Series.
Molenaar, Peter C. M.; And Others
1992-01-01
The dynamic factor model proposed by P. C. Molenaar (1985) is exhibited, and a dynamic nonstationary factor model (DNFM) is constructed with latent factor series that have time-varying mean functions. The use of a DNFM is illustrated using data from a television viewing habits study. (SLD)
A Phase Vocoder Based on Nonstationary Gabor Frames
DEFF Research Database (Denmark)
Ottosen, Emil Solsbæk; Dörfler, Monika
2017-01-01
We propose a new algorithm for time stretching music signals based on the theory of nonstationary Gabor frames (NSGFs). The algorithm extends the techniques of the classical phase vocoder (PV) by incorporating adaptive timefrequency (TF) representations and adaptive phase locking. The adaptive TF...
Elastic-plastic response characteristics during frequency nonstationary waves
International Nuclear Information System (INIS)
Miyama, T.; Kanda, J.; Iwasaki, R.; Sunohara, H.
1987-01-01
The purpose of this paper is to study fundamental effects of the frequency nonstationarity on the inelastic responses. First, the inelastic response characteristics are examined by applying stationary waves. Then simple representation of nonstationary characteristics is considered to general nonstationary input. The effects for frequency nonstationary response are summarized for inelastic systems. The inelastic response characteristics under white noise and simple frequency nonstationary wave were investigated, and conclusions can be summarized as follows. 1) The maximum response values for both BL model and OO model corresponds fairly well with those estimated from the energy constant law, even when R is small. For the OO model, the maximum displacement response forms a unique curve except for very small R. 2) The plastic deformation for the BL model is affected by wide frequency components, as R decreases. The plastic deformation for the OO model can be determined from the last stiffness. 3). The inelastic response of the BL model is considerably affected by the frequency nonstationarity of the input motion, while the response is less affected by the nonstationarity for OO model. (orig./HP)
Non-Stationary Dependence Structures for Spatial Extremes
Huser, Raphaë l; Genton, Marc G.
2016-01-01
been developed, and fitted to various types of data. However, a recurrent problem is the modeling of non-stationarity. In this paper, we develop non-stationary max-stable dependence structures in which covariates can be easily incorporated. Inference
Dynamic Memory Model for Non-Stationary Optimization
DEFF Research Database (Denmark)
Bendtsen, Claus Nørgaard; Krink, Thiemo
2002-01-01
Real-world problems are often nonstationary and can cause cyclic, repetitive patterns in the search landscape. For this class of problems, we introduce a new GA with dynamic explicit memory, which showed superior performance compared to a classic GA and a previously introduced memory-based GA for...
Robust Forecasting of Non-Stationary Time Series
Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.
2010-01-01
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable
Kharkov, N. S.
2017-11-01
Results of numerical modeling of the coupled nonstationary heat and mass transfer problem under conditions of a convective flow in facade system of a three-layer concrete panel for two different constructions (with ventilation channels and without) are presented. The positive effect of ventilation channels on the energy and humidity regime over a period of 12 months is shown. Used new method of replacement a solid zone (requiring specification of porosity and material structure, what complicates process of convergence of the solution) on quasi-solid in form of a multicomponent mixture (with restrictions on convection and mass fractions).
Identification of the structure parameters using short-time non-stationary stochastic excitation
Jarczewska, Kamila; Koszela, Piotr; Śniady, PaweŁ; Korzec, Aleksandra
2011-07-01
In this paper, we propose an approach to the flexural stiffness or eigenvalue frequency identification of a linear structure using a non-stationary stochastic excitation process. The idea of the proposed approach lies within time domain input-output methods. The proposed method is based on transforming the dynamical problem into a static one by integrating the input and the output signals. The output signal is the structure reaction, i.e. structure displacements due to the short-time, irregular load of random type. The systems with single and multiple degrees of freedom, as well as continuous systems are considered.
Time-frequency representation of a highly nonstationary signal via the modified Wigner distribution
Zoladz, T. F.; Jones, J. H.; Jong, J.
1992-01-01
A new signal analysis technique called the modified Wigner distribution (MWD) is presented. The new signal processing tool has been very successful in determining time frequency representations of highly non-stationary multicomponent signals in both simulations and trials involving actual Space Shuttle Main Engine (SSME) high frequency data. The MWD departs from the classic Wigner distribution (WD) in that it effectively eliminates the cross coupling among positive frequency components in a multiple component signal. This attribute of the MWD, which prevents the generation of 'phantom' spectral peaks, will undoubtedly increase the utility of the WD for real world signal analysis applications which more often than not involve multicomponent signals.
H2 emission from non-stationary magnetized bow shocks
Tram, L. N.; Lesaffre, P.; Cabrit, S.; Gusdorf, A.; Nhung, P. T.
2018-01-01
When a fast moving star or a protostellar jet hits an interstellar cloud, the surrounding gas gets heated and illuminated: a bow shock is born that delineates the wake of the impact. In such a process, the new molecules that are formed and excited in the gas phase become accessible to observations. In this paper, we revisit models of H2 emission in these bow shocks. We approximate the bow shock by a statistical distribution of planar shocks computed with a magnetized shock model. We improve on previous works by considering arbitrary bow shapes, a finite irradiation field and by including the age effect of non-stationary C-type shocks on the excitation diagram and line profiles of H2. We also examine the dependence of the line profiles on the shock velocity and on the viewing angle: we suggest that spectrally resolved observations may greatly help to probe the dynamics inside the bow shock. For reasonable bow shapes, our analysis shows that low-velocity shocks largely contribute to H2 excitation diagram. This can result in an observational bias towards low velocities when planar shocks are used to interpret H2 emission from an unresolved bow. We also report a large magnetization bias when the velocity of the planar model is set independently. Our 3D models reproduce excitation diagrams in BHR 71 and Orion bow shocks better than previous 1D models. Our 3D model is also able to reproduce the shape and width of the broad H2 1-0S(1) line profile in an Orion bow shock (Brand et al. 1989).
Non-stationary discharge patterns in motor cortex under subthalamic nucleus deep brain stimulation.
Santaniello, Sabato; Montgomery, Erwin B; Gale, John T; Sarma, Sridevi V
2012-01-01
Deep brain stimulation (DBS) of the subthalamic nucleus (STN) directly modulates the basal ganglia (BG), but how such stimulation impacts the cortex upstream is largely unknown. There is evidence of cortical activation in 6-hydroxydopamine (OHDA)-lesioned rodents and facilitation of motor evoked potentials in Parkinson's disease (PD) patients, but the impact of the DBS settings on the cortical activity in normal vs. Parkinsonian conditions is still debated. We use point process models to analyze non-stationary activation patterns and inter-neuronal dependencies in the motor and sensory cortices of two non-human primates during STN DBS. These features are enhanced after treatment with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP), which causes a consistent PD-like motor impairment, while high-frequency (HF) DBS (i.e., ≥100 Hz) strongly reduces the short-term patterns (period: 3-7 ms) both before and after MPTP treatment, and elicits a short-latency post-stimulus activation. Low-frequency DBS (i.e., ≤50 Hz), instead, has negligible effects on the non-stationary features. Finally, by using tools from the information theory [i.e., receiver operating characteristic (ROC) curve and information rate (IR)], we show that the predictive power of these models is dependent on the DBS settings, i.e., the probability of spiking of the cortical neurons (which is captured by the point process models) is significantly conditioned on the timely delivery of the DBS input. This dependency increases with the DBS frequency and is significantly larger for high- vs. low-frequency DBS. Overall, the selective suppression of non-stationary features and the increased modulation of the spike probability suggest that HF STN DBS enhances the neuronal activation in motor and sensory cortices, presumably because of reinforcement mechanisms, which perhaps involve the overlap between feedback antidromic and feed-forward orthodromic responses along the BG-thalamo-cortical loop.
Online updating and uncertainty quantification using nonstationary output-only measurement
Yuen, Ka-Veng; Kuok, Sin-Chi
2016-01-01
Extended Kalman filter (EKF) is widely adopted for state estimation and parametric identification of dynamical systems. In this algorithm, it is required to specify the covariance matrices of the process noise and measurement noise based on prior knowledge. However, improper assignment of these noise covariance matrices leads to unreliable estimation and misleading uncertainty estimation on the system state and model parameters. Furthermore, it may induce diverging estimation. To resolve these problems, we propose a Bayesian probabilistic algorithm for online estimation of the noise parameters which are used to characterize the noise covariance matrices. There are three major appealing features of the proposed approach. First, it resolves the divergence problem in the conventional usage of EKF due to improper choice of the noise covariance matrices. Second, the proposed approach ensures the reliability of the uncertainty quantification. Finally, since the noise parameters are allowed to be time-varying, nonstationary process noise and/or measurement noise are explicitly taken into account. Examples using stationary/nonstationary response of linear/nonlinear time-varying dynamical systems are presented to demonstrate the efficacy of the proposed approach. Furthermore, comparison with the conventional usage of EKF will be provided to reveal the necessity of the proposed approach for reliable model updating and uncertainty quantification.
International Nuclear Information System (INIS)
Lin, Chang Sheng; Chiang, Dar Yun
2012-01-01
Modal identification is considered from response data of structural system under nonstationary ambient vibration. In a previous paper, we showed that by assuming the ambient excitation to be nonstationary white noise in the form of a product model, the nonstationary response signals can be converted into free-vibration data via the correlation technique. In the present paper, if the ambient excitation can be modeled as a nonstationary white noise in the form of a product model, then the nonstationary cross random decrement signatures of structural response evaluated at any fixed time instant are shown theoretically to be proportional to the nonstationary cross-correlation functions. The practical problem of insufficient data samples available for evaluating nonstationary random decrement signatures can be approximately resolved by first extracting the amplitude-modulating function from the response and then transforming the nonstationary responses into stationary ones. Modal-parameter identification can then be performed using the Ibrahim time-domain technique, which is effective at identifying closely spaced modes. The theory proposed can be further extended by using the filtering concept to cover the case of nonstationary color excitations. Numerical simulations confirm the validity of the proposed method for identification of modal parameters from nonstationary ambient response data
International Nuclear Information System (INIS)
Mysenkov, A.I.
1979-01-01
The MOST-7 program intended for calculating nonstationary emergency models of a nuclear steam generating plant (NSGP) with a WWER reactor is considered in detail. The program consists of the main MOST-7 subprogram, two main subprograms and 98 subprograms-functions. The MOST-7 program is written in the FORTRAN language and realized at the BESM-6 computer. Program storage capacity in the BESM-6 amounts to 73400 words. Primary information input into the program is carried out by means of information input operator from punched cards and DATA operator. Parameter lists, introduced both from punched cards and by means of DATA operator are tabulated. The procedure of calculational result output into printing and plotting devices is considered. Given is an example of calculating the nonstationary process, related to the loss of power in six main circulating pumps for NSGP with the WWER-440 reactor
Study on statistical analysis of nonlinear and nonstationary reactor noises
International Nuclear Information System (INIS)
Hayashi, Koji
1993-03-01
For the purpose of identification of nonlinear mechanism and diagnosis of nuclear reactor systems, analysis methods for nonlinear reactor noise have been studied. By adding newly developed approximate response function to GMDH, a conventional nonlinear identification method, a useful method for nonlinear spectral analysis and identification of nonlinear mechanism has been established. Measurement experiment and analysis were performed on the reactor power oscillation observed in the NSRR installed at the JAERI and the cause of the instability was clarified. Furthermore, the analysis and data recording methods for nonstationary noise have been studied. By improving the time resolution of instantaneous autoregressive spectrum, a method for monitoring and diagnosis of operational status of nuclear reactor has been established. A preprocessing system for recording of nonstationary reactor noise was developed and its usability was demonstrated through a measurement experiment. (author) 139 refs
Inferential framework for non-stationary dynamics: theory and applications
International Nuclear Information System (INIS)
Duggento, Andrea; Luchinsky, Dmitri G; McClintock, Peter V E; Smelyanskiy, Vadim N
2009-01-01
An extended Bayesian inference framework is presented, aiming to infer time-varying parameters in non-stationary nonlinear stochastic dynamical systems. The convergence of the method is discussed. The performance of the technique is studied using, as an example, signal reconstruction for a system of neurons modeled by FitzHugh–Nagumo oscillators: it is applied to reconstruction of the model parameters and elements of the measurement matrix, as well as to inference of the time-varying parameters of the non-stationary system. It is shown that the proposed approach is able to reconstruct unmeasured (hidden) variables of the system, to determine the model parameters, to detect stepwise changes of control parameters for each oscillator and to track the continuous evolution of the control parameters in the adiabatic limit
Compounding approach for univariate time series with nonstationary variances
Schäfer, Rudi; Barkhofen, Sonja; Guhr, Thomas; Stöckmann, Hans-Jürgen; Kuhl, Ulrich
2015-12-01
A defining feature of nonstationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for long time horizons, however, averages over the time-dependent variances. To model the long-term statistical behavior, we compound the local distribution with the distribution of its parameters. Here, we consider two concrete, but diverse, examples of such nonstationary systems: the turbulent air flow of a fan and a time series of foreign exchange rates. Our main focus is to empirically determine the appropriate parameter distribution for the compounding approach. To this end, we extract the relevant time scales by decomposing the time signals into windows and determine the distribution function of the thus obtained local variances.
Nonstationary ARCH and GARCH with t-distributed Innovations
DEFF Research Database (Denmark)
Pedersen, Rasmus Søndergaard; Rahbek, Anders
Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t-distribut......Consistency and asymptotic normality are established for the maximum likelihood estimators in the nonstationary ARCH and GARCH models with general t-distributed innovations. The results hold for joint estimation of (G)ARCH effects and the degrees of freedom parameter parametrizing the t......-distribution. With T denoting sample size, classic square-root T-convergence is shown to hold with closed form expressions for the multivariate covariances....
Deviations from uniform power law scaling in nonstationary time series
Viswanathan, G. M.; Peng, C. K.; Stanley, H. E.; Goldberger, A. L.
1997-01-01
A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.
A Novel Simulation Model for Nonstationary Rice Fading Channels
Directory of Open Access Journals (Sweden)
Kaili Jiang
2018-01-01
Full Text Available In this paper, we propose a new simulator for nonstationary Rice fading channels under nonisotropic scattering scenarios, as well as the improved computation method of simulation parameters. The new simulator can also be applied on generating Rayleigh fading channels by adjusting parameters. The proposed simulator takes into account the smooth transition of fading phases between the adjacent channel states. The time-variant statistical properties of the proposed simulator, that is, the probability density functions (PDFs of envelope and phase, autocorrelation function (ACF, and Doppler power spectrum density (DPSD, are also analyzed and derived. Simulation results have demonstrated that our proposed simulator provides good approximation on the statistical properties with the corresponding theoretical ones, which indicates its usefulness for the performance evaluation and validation of the wireless communication systems under nonstationary and nonisotropic scenarios.
ADSL Transceivers Applying DSM and Their Nonstationary Noise Robustness
Directory of Open Access Journals (Sweden)
Bostoen Tom
2006-01-01
Full Text Available Dynamic spectrum management (DSM comprises a new set of techniques for multiuser power allocation and/or detection in digital subscriber line (DSL networks. At the Alcatel Research and Innovation Labs, we have recently developed a DSM test bed, which allows the performance of DSM algorithms to be evaluated in practice. With this test bed, we have evaluated the performance of a DSM level-1 algorithm known as iterative water-filling in an ADSL scenario. This paper describes the results of, on the one hand, the performance gains achieved with iterative water-filling, and, on the other hand, the nonstationary noise robustness of DSM-enabled ADSL modems. It will be shown that DSM trades off nonstationary noise robustness for performance improvements. A new bit swap procedure is then introduced to increase the noise robustness when applying DSM.
Network simulation of nonstationary ionic transport through liquid junctions
International Nuclear Information System (INIS)
Castilla, J.; Horno, J.
1993-01-01
Nonstationary ionic transport across the liquid junctions has been studied using Network Thermodynamics. A network model for the time-dependent Nernst-Plack-Poisson system of equation is proposed. With this network model and the electrical circuit simulation program PSPICE, the concentrations, charge density, and electrical potentials, at short times, have been simulated for the binary system NaCl/NaCl. (Author) 13 refs
On the dynamics of non-stationary binary stellar systems
International Nuclear Information System (INIS)
Bekov, A. A.; Bejsekov, A.N.; Aldibaeva, L.T.
2005-01-01
The motion of test body in the external gravitational field of the binary stellar system with slowly variable some physical parameters of radiating components is considered on the base of restricted non-stationary photo-gravitational three and two bodies problem. The family of polar and coplanar solutions are obtained. These solutions give the possibility of the dynamical and structure interpretation of the binary young evolving stars and galaxies. (author)
Robust Forecasting of Non-Stationary Time Series
Croux, C.; Fried, R.; Gijbels, I.; Mahieu, K.
2010-01-01
This paper proposes a robust forecasting method for non-stationary time series. The time series is modelled using non-parametric heteroscedastic regression, and fitted by a localized MM-estimator, combining high robustness and large efficiency. The proposed method is shown to produce reliable forecasts in the presence of outliers, non-linearity, and heteroscedasticity. In the absence of outliers, the forecasts are only slightly less precise than those based on a localized Least Squares estima...
A Generalized Framework for Non-Stationary Extreme Value Analysis
Ragno, E.; Cheng, L.; Sadegh, M.; AghaKouchak, A.
2017-12-01
Empirical trends in climate variables including precipitation, temperature, snow-water equivalent at regional to continental scales are evidence of changes in climate over time. The evolving climate conditions and human activity-related factors such as urbanization and population growth can exert further changes in weather and climate extremes. As a result, the scientific community faces an increasing demand for updated appraisal of the time-varying climate extremes. The purpose of this study is to offer a robust and flexible statistical tool for non-stationary extreme value analysis which can better characterize the severity and likelihood of extreme climatic variables. This is critical to ensure a more resilient environment in a changing climate. Following the positive feedback on the first version of Non-Stationary Extreme Value Analysis (NEVA) Toolbox by Cheng at al. 2014, we present an improved version, i.e. NEVA2.0. The upgraded version herein builds upon a newly-developed hybrid evolution Markov Chain Monte Carlo (MCMC) approach for numerical parameters estimation and uncertainty assessment. This addition leads to a more robust uncertainty estimates of return levels, return periods, and risks of climatic extremes under both stationary and non-stationary assumptions. Moreover, NEVA2.0 is flexible in incorporating any user-specified covariate other than the default time-covariate (e.g., CO2 emissions, large scale climatic oscillation patterns). The new feature will allow users to examine non-stationarity of extremes induced by physical conditions that underlie the extreme events (e.g. antecedent soil moisture deficit, large-scale climatic teleconnections, urbanization). In addition, the new version offers an option to generate stationary and/or non-stationary rainfall Intensity - Duration - Frequency (IDF) curves that are widely used for risk assessment and infrastructure design. Finally, a Graphical User Interface (GUI) of the package is provided, making NEVA
Nonstationary heat flow in the piston of the turbocharged engine
Directory of Open Access Journals (Sweden)
Piotr GUSTOF
2010-01-01
Full Text Available In this study the numeric computations of nonstationary heat flow in form of temperature distribution on characteristic surfaces of the piston of the turbocharged engine at the beginning phase its work was presented. The computations were performed for fragmentary load engine by means of the two-zone combustion model, the boundary conditions of III kind and the finite elements method (FEM by using of COSMOS/M program.
Testing for long memory in potentially nonstationary perturbed fractional processes
DEFF Research Database (Denmark)
Nielsen, Frank; Frederiksen, Per S.
¤er simulation results that show good size properties of the tests, with power against spurious long memory. An empirical study of daily log-squared returns series of exchange rates and DJIA30 stocks shows that indeed there is long memory in exchange rate volatility and stock return volatility....
Identification of Non-Stationary Magnetic Field Sources Using the Matching Pursuit Method
Directory of Open Access Journals (Sweden)
Beata Palczynska
2017-05-01
Full Text Available The measurements of electromagnetic field emissions, performed on board a vessel have showed that, in this specific environment, a high level of non-stationary magnetic fields (MFs is observed. The adaptive time-frequency method can be used successfully to analyze this type of measured signal. It allows one to specify the time interval in which the individual frequency components of the signal occur. In this paper, the method of identification of non-stationary MF sources based on the matching pursuit (MP algorithm is presented. It consists of the decomposition of an examined time-waveform into the linear expansion of chirplet atoms and the analysis of the matrix of their parameters. The main feature of the proposed method is the modification of the chirplet’s matrix in a way that atoms, whose normalized energies are lower than a certain threshold, will be rejected. On the time-frequency planes of the spectrograms, obtained separately for each remaining chirlpet, it can clearly identify the time-frequency structures appearing in the examined signal. The choice of a threshold defines the computing speed and precision of the performed analysis. The method was implemented in the virtual application and used for processing real data, obtained from measurements of time-vary MF emissions onboard a ship.
Around and about an application of the GAMLSS package to non-stationary flood frequency analysis
Debele, S. E.; Bogdanowicz, E.; Strupczewski, W. G.
2017-08-01
The non-stationarity of hydrologic processes due to climate change or human activities is challenging for the researchers and practitioners. However, the practical requirements for taking into account non-stationarity as a support in decision-making procedures exceed the up-to-date development of the theory and the of software. Currently, the most popular and freely available software package that allows for non-stationary statistical analysis is the GAMLSS (generalized additive models for location, scale and shape) package. GAMLSS has been used in a variety of fields. There are also several papers recommending GAMLSS in hydrological problems; however, there are still important issues which have not previously been discussed concerning mainly GAMLSS applicability not only for research and academic purposes, but also in a design practice. In this paper, we present a summary of our experiences in the implementation of GAMLSS to non-stationary flood frequency analysis, highlighting its advantages and pointing out weaknesses with regard to methodological and practical topics.
Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series
Vicente, Raul; Díaz-Pernas, Francisco J.; Wibral, Michael
2014-01-01
Information theory allows us to investigate information processing in neural systems in terms of information transfer, storage and modification. Especially the measure of information transfer, transfer entropy, has seen a dramatic surge of interest in neuroscience. Estimating transfer entropy from two processes requires the observation of multiple realizations of these processes to estimate associated probability density functions. To obtain these necessary observations, available estimators typically assume stationarity of processes to allow pooling of observations over time. This assumption however, is a major obstacle to the application of these estimators in neuroscience as observed processes are often non-stationary. As a solution, Gomez-Herrero and colleagues theoretically showed that the stationarity assumption may be avoided by estimating transfer entropy from an ensemble of realizations. Such an ensemble of realizations is often readily available in neuroscience experiments in the form of experimental trials. Thus, in this work we combine the ensemble method with a recently proposed transfer entropy estimator to make transfer entropy estimation applicable to non-stationary time series. We present an efficient implementation of the approach that is suitable for the increased computational demand of the ensemble method's practical application. In particular, we use a massively parallel implementation for a graphics processing unit to handle the computationally most heavy aspects of the ensemble method for transfer entropy estimation. We test the performance and robustness of our implementation on data from numerical simulations of stochastic processes. We also demonstrate the applicability of the ensemble method to magnetoencephalographic data. While we mainly evaluate the proposed method for neuroscience data, we expect it to be applicable in a variety of fields that are concerned with the analysis of information transfer in complex biological, social, and
4th International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2016-01-01
The book provides readers with a snapshot of recent research and technological trends in the field of condition monitoring of machinery working under a broad range of operating conditions. Each chapter, accepted after a rigorous peer-review process, reports on an original piece of work presented and discussed at the 4th International Conference on Condition Monitoring of Machinery in Non-stationary Operations, CMMNO 2014, held on December 15-16, 2014, in Lyon, France. The contributions have been grouped into three different sections according to the main subfield (signal processing, data mining, or condition monitoring techniques) they are related to. The book includes both theoretical developments as well as a number of industrial case studies, in different areas including, but not limited to: noise and vibration; vibro-acoustic diagnosis; signal processing techniques; diagnostic data analysis; instantaneous speed identification; monitoring and diagnostic systems; and dynamic and fault modeling. This book no...
Bi, Chuan-Xing; Geng, Lin; Zhang, Xiao-Zheng
2016-05-01
In the sound field with multiple non-stationary sources, the measured pressure is the sum of the pressures generated by all sources, and thus cannot be used directly for studying the vibration and sound radiation characteristics of every source alone. This paper proposes a separation model based on the interpolated time-domain equivalent source method (ITDESM) to separate the pressure field belonging to every source from the non-stationary multi-source sound field. In the proposed method, ITDESM is first extended to establish the relationship between the mixed time-dependent pressure and all the equivalent sources distributed on every source with known location and geometry information, and all the equivalent source strengths at each time step are solved by an iterative solving process; then, the corresponding equivalent source strengths of one interested source are used to calculate the pressure field generated by that source alone. Numerical simulation of two baffled circular pistons demonstrates that the proposed method can be effective in separating the non-stationary pressure generated by every source alone in both time and space domains. An experiment with two speakers in a semi-anechoic chamber further evidences the effectiveness of the proposed method.
Park, Junehyeong; Sung, Jang Hyun; Lim, Yoon-Jin; Kang, Hyun-Suk
2018-05-01
The widely used meteorological drought index, the Standardized Precipitation Index (SPI), basically assumes stationarity, but recent changes in the climate have led to a need to review this hypothesis. In this study, a new non-stationary SPI that considers not only the modified probability distribution parameter but also the return period under the non-stationary process was proposed. The results were evaluated for two severe drought cases during the last 10 years in South Korea. As a result, SPIs considered that the non-stationary hypothesis underestimated the drought severity than the stationary SPI despite that these past two droughts were recognized as significantly severe droughts. It may be caused by that the variances of summer and autumn precipitation become larger over time then it can make the probability distribution wider than before. This implies that drought expressions by statistical index such as SPI can be distorted by stationary assumption and cautious approach is needed when deciding drought level considering climate changes.
Park, Jeryang; Rao, P Suresh C
2014-11-15
We present here a conceptual model and analysis of complex systems using hypothetical cases of regime shifts resulting from temporal non-stationarity in attractor strengths, and then present selected published cases to illustrate such regime shifts in hydrologic systems (shallow aquatic ecosystems; water table shifts; soil salinization). Complex systems are dynamic and can exist in two or more stable states (or regimes). Temporal variations in state variables occur in response to fluctuations in external forcing, which are modulated by interactions among internal processes. Combined effects of external forcing and non-stationary strengths of alternative attractors can lead to shifts from original to alternate regimes. In systems with bi-stable states, when the strengths of two competing attractors are constant in time, or are non-stationary but change in a linear fashion, regime shifts are found to be temporally stationary and only controlled by the characteristics of the external forcing. However, when attractor strengths change in time non-linearly or vary stochastically, regime shifts in complex systems are characterized by non-stationary probability density functions (pdfs). We briefly discuss implications and challenges to prediction and management of hydrologic complex systems. Copyright © 2014 Elsevier B.V. All rights reserved.
Pieciak, Tomasz; Aja-Fernandez, Santiago; Vegas-Sanchez-Ferrero, Gonzalo
2017-10-01
Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e., it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.
Optimizing a Military Supply Chain in the Presence of Random, Non-Stationary Demands
National Research Council Canada - National Science Library
Yew
2003-01-01
... logistics supply chain that satisfies uncertain, non-stationary demands, while taking into account the volatility and singularity of military operations This research focuses on the development...
3rd International Conference on Condition Monitoring of Machinery in Non-Stationary Operations
Rubini, Riccardo; D'Elia, Gianluca; Cocconcelli, Marco; Chaari, Fakher; Zimroz, Radoslaw; Bartelmus, Walter; Haddar, Mohamed
2014-01-01
This book presents the processings of the third edition of the Condition Monitoring of Machinery in Non-Stationary Operations (CMMNO13) which was held in Ferrara, Italy. This yearly event merges an international community of researchers who met – in 2011 in Wroclaw (Poland) and in 2012 in Hammamet (Tunisia) – to discuss issues of diagnostics of rotating machines operating in complex motion and/or load conditions. The growing interest of the industrial world on the topics covered by the CMMNO13 involves the fields of packaging, automotive, agricultural, mining, processing and wind machines in addition to that of the systems for data acquisition.The participation of speakers and visitors from industry makes the event an opportunity for immediate assessment of the potential applications of advanced methodologies for the signal analysis. Signals acquired from machines often contain contributions from several different components as well as noise. Therefore, the major challenge of condition monitoring is to po...
Autocalibration method for non-stationary CT bias correction.
Vegas-Sánchez-Ferrero, Gonzalo; Ledesma-Carbayo, Maria J; Washko, George R; Estépar, Raúl San José
2018-02-01
Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases. Copyright © 2017 Elsevier B.V. All rights reserved.
International Nuclear Information System (INIS)
Kuznetsov, Yu.N.; Kalinin, E.I.; Naumov, M.A.
1980-01-01
The effect of variability of heat duty on the characteristics of heat exchange in ring channels and rod bundles is investigated with analytical methods. The plotting of calculation formulae for non-stationary heat exchange in an annular channel at a jump of heat duty is carried out on the basis of the method of the effect function. The formulae obtained permit to accomplish technical calculations of the processes of non-stationary heat exchange in annular channels in the case of any alterations of thermal duty in time, at any moment of time, for any channel cross section (including the entrance heat section) in a wide range of geometric and regime parameters of the turbulent current of a coolant. According to preliminary estimates, calculation results differ from the results oi a numerical solution less than 5%. The approach considered permits to transfer the data on the non-stationary heat exchange in annular channels in the case of changing the heat duty in time, in the case of a non-stationary heat exchange in longitudinally flown not very dense and infinite rod bundles
Detrending of non-stationary noise data by spline techniques
International Nuclear Information System (INIS)
Behringer, K.
1989-11-01
An off-line method for detrending non-stationary noise data has been investigated. It uses a least squares spline approximation of the noise data with equally spaced breakpoints. Subtraction of the spline approximation from the noise signal at each data point gives a residual noise signal. The method acts as a high-pass filter with very sharp frequency cutoff. The cutoff frequency is determined by the breakpoint distance. The steepness of the cutoff is controlled by the spline order. (author) 12 figs., 1 tab., 5 refs
Guo, L.; Van der Wegen, M.; Jay, D.A.; Matte, P.; Wang, Z.B.; Roelvink, J.A.; He, Q.
2015-01-01
River-tide dynamics remain poorly understood, in part because conventional harmonic analysis (HA) does not cope effectively with nonstationary signals. To explore nonstationary behavior of river tides and the modulation effects of river discharge, this work analyzes tidal signals in the Yangtze
Directory of Open Access Journals (Sweden)
V. K. Bityukov
2016-01-01
Full Text Available Analytical study of the processes of heat conduction is one of the main topics of modern engineering research in engineering, energy, nuclear industry, process chemical, construction, textile, food, geological and other industries. Suffice to say that almost all processes in one degree or another are related to change in the temperature condition and the transfer of warmth. It should also be noted that engineering studies of the kinetics of a range of physical and chemical processes are similar to the problems of stationary and nonstationary heat transfer. These include the processes of diffusions, sedimentation, viscous flow, slowing down the neutrons, flow of fluids through a porous medium, electric fluctuations, adsorption, drying, burning, etc. There are various methods for solving the classical boundary value problems of nonstationary heat conduction and problems of the generalized type: the method of separation of variables (Fourier method method; the continuation method; the works solutions; the Duhamel's method; the integral transformations method; the operating method; the method of green's functions (stationary and non-stationary thermal conductivity; the reflection method (method source. In this paper, based on the consistent application of the Laplace transform on the dimensionless time θ and finite sine integral transformation in the spatial coordinates X and Y solves the problem of unsteady temperature distribution on the mechanism of heat conduction in a parallelepiped with boundary conditions of first kind. As a result we have the analytical solution of the temperature distribution in the parallelepiped to a conductive mode free convection, when one of the side faces of the parallelepiped is maintained at a constant temperature, and the others with the another same constant temperature.
Nonstationary Heat Conduction in Atomic Systems
Singh, Amit K.
reproduce the molecular dynamics results for a short-duration heat pulse where wavelike propagation of heat is observed thereby confirming the existence of second sound in argon. Implementations of the TPI method in MATLAB are available as part of the supplementary material. 2. The second major work of the thesis is to look into the following problem. The direct method for computing thermal conductivity in nonequilibrium molecular dynamics gives rise to an artificial Kapitza resistance at the interface between thermostatted and unthermostatted regions. This resistance, which depends on the system size and the thermostat parameters, creates discontinuous jumps in the temperature and heat flux across the interface and therefore affects the measured thermal conductivity. In this part, we propose a phenomenological relation for the Kapitza resistance that can be used to extract a value for the bulk thermal conductivity, which is independent of the system size and thermostat details. We also provide insight into the Kapitza phenomenon resulting from numerical thermostatting. 3. This constitutes our third part of the thesis. Silicon (001) surfaces in non-equilibrium molecular dynamics (NEMD) simulations above a critical transformation temperature undergo a reconstruction from the ideal diamond crystalline surface to a reconstructed structure involving the formation of rows of dimers along a direction. This process is accompanied by latent heat release that in NEMD simulations results in a dramatic increase in temperature of nanobeams that cross the transformation temperature as they are heated. To model this behavior, we propose a hybrid continuum partial differential equation for non-Fourier heat transfer coupled with a stochastic kinetic Monte Carlo (KMC) algorithm to account for latent heat release. An input to the method is the energy barrier for dimerization, which is computed separately using nudged elastic band calculations. The time-dependent temperature profiles along
International Nuclear Information System (INIS)
Winkler, R.; Wilhelm, J.
A detailed description is presented of calculating the nonstationary electron distribution function in a weakly ionized collision-dominated plasma from the Boltzmann kinetic equation respecting the effects of the time-dependent electric field, collision processes and the electron formation and loss. The finite difference approximation was used for numerical solution. Using the Crank-Nicolson method and parabolic interpolation between the grid points the Boltzmann equation was transformed to a system of linear equations which was then solved by iterations at a preset accuracy. Using the calculated distribution function values, the macroscopic plasma parameters were determined and the balance of electron density and energy checked in each time step. The mathematical procedure is illustrated using a neon plasma perturbed by a rectangular electric pulse. The time development shown of the distribution function at moments when the pulse was switched on and off demonstrates the great stability of the numerical solution. (J.U.)
Instantaneous Purified Orbit: A New Tool for Analysis of Nonstationary Vibration of Rotor System
Directory of Open Access Journals (Sweden)
Shi Dongfeng
2001-01-01
Full Text Available In some circumstances, vibration signals of large rotating machinery possess time-varying characteristics to some extent. Traditional diagnosis methods, such as FFT spectrum and orbit diagram, are confronted with a huge challenge to deal with this problem. This work aims at studying the four intrinsic drawbacks of conventional vibration signal processing method and instantaneous purified orbit (IPO on the basis of improved Fourier spectrum (IFS to analyze nonstationary vibration. On account of integration, the benefits of short period Fourier transform (SPFT and regular holospectrum, this method can intuitively reflect vibration characteristics of’a rotor system by means of parameter analysis for corresponding frequency ellipses. Practical examples, such as transient vibration in run-up stages and bistable condition of rotor show that IPO is a powerful tool for diagnosis and analysis of the vibration behavior of rotor systems.
Is the Labour Force Participation Rate Non-Stationary in Romania?
Directory of Open Access Journals (Sweden)
Tiwari Aviral Kumar
2015-01-01
Full Text Available The purpose of this paper is to test hysteresis of the Romanian labour force participation rate, by using time series data, with quarterly frequency, covering the period 1999Q1-2013Q4. The main results reveal that the Romanian labour force participation rate is a nonlinear process and has a partial unit root (i.e. it is stationary in the first regime and non-stationary in the second one, the main breaking point being registered around year 2005. In this context, the value of using unemployment rate as an indicator for capturing joblessness in this country is debatable. Starting from 2005, the participation rate has not followed long-term changes in unemployment rate, the disturbances having permanent effects on labour force participation rate.
International Nuclear Information System (INIS)
Chen, Shih-Hung; Chen, Liu
2013-01-01
The nonstationary oscillation of the gyrotron backward wave oscillator (gyro-BWO) with cylindrical interaction structure was studied utilizing both steady-state analyses and time-dependent simulations. Comparisons of the numerical results reveal that the gyro-BWO becomes nonstationary when the trailing field structure completely forms due to the dephasing energetic electrons. The backward propagation of radiated waves with a lower resonant frequency from the trailing field structure interferes with the main internal feedback loop, thereby inducing the nonstationary oscillation of the gyro-BWO. The nonstationary gyro-BWO exhibits the same spectral pattern of modulated oscillations with a constant frequency separation between the central frequency and sidebands throughout the whole system. The frequency separation is found to be scaled with the square root of the maximum field amplitude, thus further demonstrating that the nonstationary oscillation of the gyro-BWO is associated with the beam-wave resonance detuning
Incremental learning of concept drift in nonstationary environments.
Elwell, Ryan; Polikar, Robi
2011-10-01
We introduce an ensemble of classifiers-based approach for incremental learning of concept drift, characterized by nonstationary environments (NSEs), where the underlying data distributions change over time. The proposed algorithm, named Learn(++). NSE, learns from consecutive batches of data without making any assumptions on the nature or rate of drift; it can learn from such environments that experience constant or variable rate of drift, addition or deletion of concept classes, as well as cyclical drift. The algorithm learns incrementally, as other members of the Learn(++) family of algorithms, that is, without requiring access to previously seen data. Learn(++). NSE trains one new classifier for each batch of data it receives, and combines these classifiers using a dynamically weighted majority voting. The novelty of the approach is in determining the voting weights, based on each classifier's time-adjusted accuracy on current and past environments. This approach allows the algorithm to recognize, and act accordingly, to the changes in underlying data distributions, as well as to a possible reoccurrence of an earlier distribution. We evaluate the algorithm on several synthetic datasets designed to simulate a variety of nonstationary environments, as well as a real-world weather prediction dataset. Comparisons with several other approaches are also included. Results indicate that Learn(++). NSE can track the changing environments very closely, regardless of the type of concept drift. To allow future use, comparison and benchmarking by interested researchers, we also release our data used in this paper. © 2011 IEEE
Sampling design optimisation for rainfall prediction using a non-stationary geostatistical model
Wadoux, Alexandre M. J.-C.; Brus, Dick J.; Rico-Ramirez, Miguel A.; Heuvelink, Gerard B. M.
2017-09-01
The accuracy of spatial predictions of rainfall by merging rain-gauge and radar data is partly determined by the sampling design of the rain-gauge network. Optimising the locations of the rain-gauges may increase the accuracy of the predictions. Existing spatial sampling design optimisation methods are based on minimisation of the spatially averaged prediction error variance under the assumption of intrinsic stationarity. Over the past years, substantial progress has been made to deal with non-stationary spatial processes in kriging. Various well-documented geostatistical models relax the assumption of stationarity in the mean, while recent studies show the importance of considering non-stationarity in the variance for environmental processes occurring in complex landscapes. We optimised the sampling locations of rain-gauges using an extension of the Kriging with External Drift (KED) model for prediction of rainfall fields. The model incorporates both non-stationarity in the mean and in the variance, which are modelled as functions of external covariates such as radar imagery, distance to radar station and radar beam blockage. Spatial predictions are made repeatedly over time, each time recalibrating the model. The space-time averaged KED variance was minimised by Spatial Simulated Annealing (SSA). The methodology was tested using a case study predicting daily rainfall in the north of England for a one-year period. Results show that (i) the proposed non-stationary variance model outperforms the stationary variance model, and (ii) a small but significant decrease of the rainfall prediction error variance is obtained with the optimised rain-gauge network. In particular, it pays off to place rain-gauges at locations where the radar imagery is inaccurate, while keeping the distribution over the study area sufficiently uniform.
Enhancement of Non-Stationary Speech using Harmonic Chirp Filters
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2015-01-01
In this paper, the issue of single channel speech enhancement of non-stationary voiced speech is addressed. The non-stationarity of speech is well known, but state of the art speech enhancement methods assume stationarity within frames of 20–30 ms. We derive optimal distortionless filters that take...... the non-stationarity nature of voiced speech into account via linear constraints. This is facilitated by imposing a harmonic chirp model on the speech signal. As an implicit part of the filter design, the noise statistics are also estimated based on the observed signal and parameters of the harmonic chirp...... model. Simulations on real speech show that the chirp based filters perform better than their harmonic counterparts. Further, it is seen that the gain of using the chirp model increases when the estimated chirp parameter is big corresponding to periods in the signal where the instantaneous fundamental...
Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals
Hedayatifar, L.; Vahabi, M.; Jafari, G. R.
2011-08-01
When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.
Nonstationary Transient Vibroacoustic Response of a Beam Structure
Caimi, R. E.; Margasahayam, R. N.; Nayfeh, Jamal F.
1997-01-01
This study consists of an investigation into the nonstationary transient response of the Verification Test Article (VETA) when subjected to random acoustic excitation. The goal is to assess excitation models that can be used in the design of structures and equipment when knowledge of the structure and the excitation is limited. The VETA is an instrumented cantilever beam that was exposed to acoustic loading during five Space Shuttle launches. The VETA analytical structural model response is estimated using the direct averaged power spectral density and the normalized pressure spectra methods. The estimated responses are compared to the measured response of the VETA. These comparisons are discussed with a focus on prediction conservatism and current design practice.
Gravitational entropy of nonstationary black holes and spherical shells
International Nuclear Information System (INIS)
Hiscock, W.A.
1989-01-01
The problem of defining the gravitational entropy of a nonstationary black hole is considered in a simple model consisting of a spherical shell which collapses into a preexisting black hole. The second law of black-hole mechanics strongly suggests identifying one-quarter of the area of the event horizon as the gravitational entropy of the system. It is, however, impossible to accurately locate the position of the global event horizon using only local measurements. In order to maintain a local thermodynamics, it is suggested that the entropy of the black hole be identified with one-quarter the area of the apparent horizon. The difference between the event-horizon entropy (to the extent it can be determined) and the apparent-horizon entropy may then be interpreted as the gravitational entropy of the collapsing shell. The total (event-horizon) gravitational entropy evolves in a smooth (C 0 ) fashion, even in the presence of δ-functional shells of matter
Non-stationary vibrations of a thin viscoelastic orthotropic beam
Czech Academy of Sciences Publication Activity Database
Adámek, V.; Valeš, František; Tikal, B.
2009-01-01
Roč. 71, č. 12 (2009), e2569-e2576 ISSN 0362-546X R&D Projects: GA ČR(CZ) GA101/07/0946 Institutional research plan: CEZ:AV0Z20760514 Keywords : thin beam * non-stationary vibration * analytical solution Subject RIV: BI - Acoustics Impact factor: 1.487, year: 2009 http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6V0Y-4WB3N8S-4&_user=640952&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1156243286&_rerunOrigin= google &_acct=C000034318&_version=1&_urlVersion=0&_userid=640952&md5=ce096901a3382058455e822a20645820
Generalized Predictive Control for Non-Stationary Systems
DEFF Research Database (Denmark)
Palsson, Olafur Petur; Madsen, Henrik; Søgaard, Henning Tangen
1994-01-01
This paper shows how the generalized predictive control (GPC) can be extended to non-stationary (time-varying) systems. If the time-variation is slow, then the classical GPC can be used in context with an adaptive estimation procedure of a time-invariant ARIMAX model. However, in this paper prior...... knowledge concerning the nature of the parameter variations is assumed available. The GPC is based on the assumption that the prediction of the system output can be expressed as a linear combination of present and future controls. Since the Diophantine equation cannot be used due to the time......-variation of the parameters, the optimal prediction is found as the general conditional expectation of the system output. The underlying model is of an ARMAX-type instead of an ARIMAX-type as in the original version of the GPC (Clarke, D. W., C. Mohtadi and P. S. Tuffs (1987). Automatica, 23, 137-148) and almost all later...
A Phase Vocoder Based on Nonstationary Gabor Frames
DEFF Research Database (Denmark)
Ottosen, Emil Solsbæk; Dörfler, Monika
2017-01-01
We propose a new algorithm for time stretching music signals based on the theory of nonstationary Gabor frames (NSGFs). The algorithm extends the techniques of the classical phase vocoder (PV) by incorporating adaptive timefrequency (TF) representations and adaptive phase locking. The adaptive TF...... representations imply good time resolution for the onsets of attack transients and good frequency resolution for the sinusoidal components. We estimate the phase values only at peak channels and the remaining phases are then locked to the values of the peaks in an adaptive manner. During attack transients we keep...... that with just three times as many TF coefficients as signal samples, artifacts such as phasiness and transient smearing can be greatly reduced compared to the classical PV. The proposed algorithm is tested on both synthetic and real world signals and compared with state of the art algorithms in a reproducible...
Nonstationary signals phase-energy approach-theory and simulations
Klein, R; Braun, S; 10.1006/mssp.2001.1398
2001-01-01
Modern time-frequency methods are intended to deal with a variety of nonstationary signals. One specific class, prevalent in the area of rotating machines, is that of harmonic signals of varying frequencies and amplitude. This paper presents a new adaptive phase-energy (APE) approach for time-frequency representation of varying harmonic signals. It is based on the concept of phase (frequency) paths and the instantaneous power spectral density (PSD). It is this path which represents the dynamic behaviour of the system generating the observed signal. The proposed method utilises dynamic filters based on an extended Nyquist theorem, enabling extraction of signal components with optimal signal-to-noise ratio. The APE detects the most energetic harmonic components (frequency paths) in the analysed signal. Tests on simulated signals show the superiority of the APE in resolution and resolving power as compared to STFT and wavelets wave- packet decomposition. The dynamic filters also enable the reconstruction of the ...
Directed transport of confined Brownian particles with torque
Radtke, Paul K.; Schimansky-Geier, Lutz
2012-05-01
We investigate the influence of an additional torque on the motion of Brownian particles confined in a channel geometry with varying width. The particles are driven by random fluctuations modeled by an Ornstein-Uhlenbeck process with given correlation time τc. The latter causes persistent motion and is implemented as (i) thermal noise in equilibrium and (ii) noisy propulsion in nonequilibrium. In the nonthermal process a directed transport emerges; its properties are studied in detail with respect to the correlation time, the torque, and the channel geometry. Eventually, the transport mechanism is traced back to a persistent sliding of particles along the even boundaries in contrast to scattered motion at uneven or rough ones.
Estimation of mean-reverting oil prices: a laboratory approach
International Nuclear Information System (INIS)
Bjerksund, P.; Stensland, G.
1993-12-01
Many economic decision support tools developed for the oil industry are based on the future oil price dynamics being represented by some specified stochastic process. To meet the demand for necessary data, much effort is allocated to parameter estimation based on historical oil price time series. The approach in this paper is to implement a complex future oil market model, and to condense the information from the model to parameter estimates for the future oil price. In particular, we use the Lensberg and Rasmussen stochastic dynamic oil market model to generate a large set of possible future oil price paths. Given the hypothesis that the future oil price is generated by a mean-reverting Ornstein-Uhlenbeck process, we obtain parameter estimates by a maximum likelihood procedure. We find a substantial degree of mean-reversion in the future oil price, which in some of our decision examples leads to an almost negligible value of flexibility. 12 refs., 2 figs., 3 tabs
Comparison of nonstationary generalized logistic models based on Monte Carlo simulation
Directory of Open Access Journals (Sweden)
S. Kim
2015-06-01
Full Text Available Recently, the evidences of climate change have been observed in hydrologic data such as rainfall and flow data. The time-dependent characteristics of statistics in hydrologic data are widely defined as nonstationarity. Therefore, various nonstationary GEV and generalized Pareto models have been suggested for frequency analysis of nonstationary annual maximum and POT (peak-over-threshold data, respectively. However, the alternative models are required for nonstatinoary frequency analysis because of analyzing the complex characteristics of nonstationary data based on climate change. This study proposed the nonstationary generalized logistic model including time-dependent parameters. The parameters of proposed model are estimated using the method of maximum likelihood based on the Newton-Raphson method. In addition, the proposed model is compared by Monte Carlo simulation to investigate the characteristics of models and applicability.
Self-adaptive change detection in streaming data with non-stationary distribution
Zhang, Xiangliang; Wang, Wei
2010-01-01
Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non
DEFF Research Database (Denmark)
Kock, Anders Bredahl
2016-01-01
We show that the adaptive Lasso is oracle efficient in stationary and nonstationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...
Approximate calculation method for integral of mean square value of nonstationary response
International Nuclear Information System (INIS)
Aoki, Shigeru; Fukano, Azusa
2010-01-01
The response of the structure subjected to nonstationary random vibration such as earthquake excitation is nonstationary random vibration. Calculating method for statistical characteristics of such a response is complicated. Mean square value of the response is usually used to evaluate random response. Integral of mean square value of the response corresponds to total energy of the response. In this paper, a simplified calculation method to obtain integral of mean square value of the response is proposed. As input excitation, nonstationary white noise and nonstationary filtered white noise are used. Integrals of mean square value of the response are calculated for various values of parameters. It is found that the proposed method gives exact value of integral of mean square value of the response.
Modeling sheep pox disease from the 1994-1998 epidemic in Evros Prefecture, Greece.
Malesios, C; Demiris, N; Abas, Z; Dadousis, K; Koutroumanidis, T
2014-10-01
Sheep pox is a highly transmissible disease which can cause serious loss of livestock and can therefore have major economic impact. We present data from sheep pox epidemics which occurred between 1994 and 1998. The data include weekly records of infected farms as well as a number of covariates. We implement Bayesian stochastic regression models which, in addition to various explanatory variables like seasonal and environmental/meteorological factors, also contain serial correlation structure based on variants of the Ornstein-Uhlenbeck process. We take a predictive view in model selection by utilizing deviance-based measures. The results indicate that seasonality and the number of infected farms are important predictors for sheep pox incidence. Copyright © 2014 Elsevier Ltd. All rights reserved.
Modeling and Forecasting Average Temperature for Weather Derivative Pricing
Directory of Open Access Journals (Sweden)
Zhiliang Wang
2015-01-01
Full Text Available The main purpose of this paper is to present a feasible model for the daily average temperature on the area of Zhengzhou and apply it to weather derivatives pricing. We start by exploring the background of weather derivatives market and then use the 62 years of daily historical data to apply the mean-reverting Ornstein-Uhlenbeck process to describe the evolution of the temperature. Finally, Monte Carlo simulations are used to price heating degree day (HDD call option for this city, and the slow convergence of the price of the HDD call can be found through taking 100,000 simulations. The methods of the research will provide a frame work for modeling temperature and pricing weather derivatives in other similar places in China.
Value of the future: Discounting in random environments
Farmer, J. Doyne; Geanakoplos, John; Masoliver, Jaume; Montero, Miquel; Perelló, Josep
2015-05-01
We analyze how to value future costs and benefits when they must be discounted relative to the present. We introduce the subject for the nonspecialist and take into account the randomness of the economic evolution by studying the discount function of three widely used processes for the dynamics of interest rates: Ornstein-Uhlenbeck, Feller, and log-normal. Besides obtaining exact expressions for the discount function and simple asymptotic approximations, we show that historical average interest rates overestimate long-run discount rates and that this effect can be large. In other words, long-run discount rates should be substantially less than the average rate observed in the past, otherwise any cost-benefit calculation would be biased in favor of the present and against interventions that may protect the future.
Fast shuttling of a particle under weak spring-constant noise of the moving trap
Lu, Xiao-Jing; Ruschhaupt, A.; Muga, J. G.
2018-05-01
We investigate the excitation of a quantum particle shuttled in a harmonic trap with weak spring-constant colored noise. The Ornstein-Uhlenbeck model for the noise correlation function describes a wide range of possible noises, in particular for short correlation times the white-noise limit examined by Lu et al. [Phys. Rev. A 89, 063414 (2014)], 10.1103/PhysRevA.89.063414 and, by averaging over correlation times, "1 /f flicker noise." We find expressions for the excitation energy in terms of static (independent of trap motion) and dynamical sensitivities, with opposite behavior with respect to shuttling time, and demonstrate that the excitation can be reduced by proper process timing and design of the trap trajectory.
Relaxometry imaging of superparamagnetic magnetite nanoparticles at ambient conditions
Finkler, Amit; Schmid-Lorch, Dominik; Häberle, Thomas; Reinhard, Friedemann; Zappe, Andrea; Slota, Michael; Bogani, Lapo; Wrachtrup, Jörg
We present a novel technique to image superparamagnetic iron oxide nanoparticles via their fluctuating magnetic fields. The detection is based on the nitrogen-vacancy (NV) color center in diamond, which allows optically detected magnetic resonance (ODMR) measurements on its electron spin structure. In combination with an atomic-force-microscope, this atomic-sized color center maps ambient magnetic fields in a wide frequency range from DC up to several GHz, while retaining a high spatial resolution in the sub-nanometer range. We demonstrate imaging of single 10 nm sized magnetite nanoparticles using this spin noise detection technique. By fitting simulations (Ornstein-Uhlenbeck process) to the data, we are able to infer additional information on such a particle and its dynamics, like the attempt frequency and the anisotropy constant. This is of high interest to the proposed application of magnetite nanoparticles as an alternative MRI contrast agent or to the field of particle-aided tumor hyperthermia.
Digital hardware implementation of a stochastic two-dimensional neuron model.
Grassia, F; Kohno, T; Levi, T
2016-11-01
This study explores the feasibility of stochastic neuron simulation in digital systems (FPGA), which realizes an implementation of a two-dimensional neuron model. The stochasticity is added by a source of current noise in the silicon neuron using an Ornstein-Uhlenbeck process. This approach uses digital computation to emulate individual neuron behavior using fixed point arithmetic operation. The neuron model's computations are performed in arithmetic pipelines. It was designed in VHDL language and simulated prior to mapping in the FPGA. The experimental results confirmed the validity of the developed stochastic FPGA implementation, which makes the implementation of the silicon neuron more biologically plausible for future hybrid experiments. Copyright © 2017 Elsevier Ltd. All rights reserved.
Hu, D. L.; Liu, X. B.
Both periodic loading and random forces commonly co-exist in real engineering applications. However, the dynamic behavior, especially dynamic stability of systems under parametric periodic and random excitations has been reported little in the literature. In this study, the moment Lyapunov exponent and stochastic stability of binary airfoil under combined harmonic and non-Gaussian colored noise excitations are investigated. The noise is simplified to an Ornstein-Uhlenbeck process by applying the path-integral method. Via the singular perturbation method, the second-order expansions of the moment Lyapunov exponent are obtained, which agree well with the results obtained by the Monte Carlo simulation. Finally, the effects of the noise and parametric resonance (such as subharmonic resonance and combination additive resonance) on the stochastic stability of the binary airfoil system are discussed.
Equations involving Malliavin calculus operators applications and numerical approximation
Levajković, Tijana
2017-01-01
This book provides a comprehensive and unified introduction to stochastic differential equations and related optimal control problems. The material is new and the presentation is reader-friendly. A major contribution of the book is the development of generalized Malliavin calculus in the framework of white noise analysis, based on chaos expansion representation of stochastic processes and its application for solving several classes of stochastic differential equations with singular data involving the main operators of Malliavin calculus. In addition, applications in optimal control and numerical approximations are discussed. The book is divided into four chapters. The first, entitled White Noise Analysis and Chaos Expansions, includes notation and provides the reader with the theoretical background needed to understand the subsequent chapters. In Chapter 2, Generalized Operators of Malliavin Calculus, the Malliavin derivative operator, the Skorokhod integral and the Ornstein-Uhlenbeck operator are introdu...
Analyzing nonstationary financial time series via hilbert-huang transform (HHT)
Huang, Norden E. (Inventor)
2008-01-01
An apparatus, computer program product and method of analyzing non-stationary time varying phenomena. A representation of a non-stationary time varying phenomenon is recursively sifted using Empirical Mode Decomposition (EMD) to extract intrinsic mode functions (IMFs). The representation is filtered to extract intrinsic trends by combining a number of IMFs. The intrinsic trend is inherent in the data and identifies an IMF indicating the variability of the phenomena. The trend also may be used to detrend the data.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-01-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods ...
Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.
2011-09-01
A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.
International Nuclear Information System (INIS)
Cao, Z.J.; Tsui, B.M.
1993-01-01
Conventional single-orbit cone beam tomography presents special problems. They include incomplete sampling and inadequate three-dimensional (3D) reconstruction algorithm. The commonly used Feldkamp reconstruction algorithm simply extends the two-dimensional (2D) fan beam algorithm to 3D cone beam geometry. A truly 3D reconstruction formulation has been derived for the single-orbit cone beam SPECT based on the 3D Fourier slice theorem. In the formulation, a nonstationary filter which depends on the distance from the central plane of the cone beam was derived. The filter is applied to the 2D projection data in directions along and normal to the axis-of-rotation. The 3D reconstruction algorithm with the nonstationary filter was evaluated using both computer simulation and experimental measurements. Significant improvement in image quality was demonstrated in terms of decreased artifacts and distortions in cone beam reconstructed images. However, compared with the Feldkamp algorithm, a five-fold increase in processing time is required. Further improvement in image quality needs complete sampling in frequency space
A New Method for Non-linear and Non-stationary Time Series Analysis:
The Hilbert Spectral Analysis
CERN. Geneva
2000-01-01
A new method for analysing non-linear and non-stationary data has been developed. The key part of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is defined as any function having the same numbers of zero crossing and extreme, and also having symmetric envelopes defined by the local maximal and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and, therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to non-linear and non-stationary processes. With the Hilbert transform, the Intrinsic Mode Functions yield instantaneous frequencies as functions of time that give sharp identifications of imbedded structures. The final presentation of the results is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Classical non-l...
Energy Technology Data Exchange (ETDEWEB)
Zhukov, A.A. [N.L. Dukhov All-Russia Research Institute of Automatics, 127055 Moscow (Russian Federation); National Research Nuclear University (MEPhI), 115409 Moscow (Russian Federation); Shapiro, D.S., E-mail: shapiro.dima@gmail.com [N.L. Dukhov All-Russia Research Institute of Automatics, 127055 Moscow (Russian Federation); V.A. Kotel' nikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, 125009 Moscow (Russian Federation); Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141700 (Russian Federation); National University of Science and Technology MISIS, 119049 Moscow (Russian Federation); Remizov, S.V. [N.L. Dukhov All-Russia Research Institute of Automatics, 127055 Moscow (Russian Federation); V.A. Kotel' nikov Institute of Radio Engineering and Electronics, Russian Academy of Sciences, 125009 Moscow (Russian Federation); Pogosov, W.V. [N.L. Dukhov All-Russia Research Institute of Automatics, 127055 Moscow (Russian Federation); Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141700 (Russian Federation); Institute for Theoretical and Applied Electrodynamics, Russian Academy of Sciences, 125412 Moscow (Russian Federation); Lozovik, Yu.E. [N.L. Dukhov All-Russia Research Institute of Automatics, 127055 Moscow (Russian Federation); National Research Nuclear University (MEPhI), 115409 Moscow (Russian Federation); Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141700 (Russian Federation); Institute of Spectroscopy, Russian Academy of Sciences, 142190 Moscow Region, Troitsk (Russian Federation)
2017-02-12
We consider a superconducting qubit coupled to the nonstationary transmission line cavity with modulated frequency taking into account energy dissipation. Previously, it was demonstrated that in the case of a single nonadiabatical modulation of a cavity frequency there are two channels of a two-level system excitation which are due to the absorption of Casimir photons and due to the counterrotating wave processes responsible for the dynamical Lamb effect. We show that the parametric periodical modulation of the resonator frequency can increase dramatically the excitation probability. Remarkably, counterrotating wave processes under such a modulation start to play an important role even in the resonant regime. Our predictions can be used to control qubit-resonator quantum states as well as to study experimentally different channels of a parametric qubit excitation. - Highlights: • Coupled qubit-resonator system under the modulation of a resonator frequency is considered. • Counterrotating terms of the Hamiltonian are of importance even in the resonance. • Qubit excited state population is highest if driving frequency matches dressed-state energy.
Can we identify non-stationary dynamics of trial-to-trial variability?
Directory of Open Access Journals (Sweden)
Emili Balaguer-Ballester
Full Text Available Identifying sources of the apparent variability in non-stationary scenarios is a fundamental problem in many biological data analysis settings. For instance, neurophysiological responses to the same task often vary from each repetition of the same experiment (trial to the next. The origin and functional role of this observed variability is one of the fundamental questions in neuroscience. The nature of such trial-to-trial dynamics however remains largely elusive to current data analysis approaches. A range of strategies have been proposed in modalities such as electro-encephalography but gaining a fundamental insight into latent sources of trial-to-trial variability in neural recordings is still a major challenge. In this paper, we present a proof-of-concept study to the analysis of trial-to-trial variability dynamics founded on non-autonomous dynamical systems. At this initial stage, we evaluate the capacity of a simple statistic based on the behaviour of trajectories in classification settings, the trajectory coherence, in order to identify trial-to-trial dynamics. First, we derive the conditions leading to observable changes in datasets generated by a compact dynamical system (the Duffing equation. This canonical system plays the role of a ubiquitous model of non-stationary supervised classification problems. Second, we estimate the coherence of class-trajectories in empirically reconstructed space of system states. We show how this analysis can discern variations attributable to non-autonomous deterministic processes from stochastic fluctuations. The analyses are benchmarked using simulated and two different real datasets which have been shown to exhibit attractor dynamics. As an illustrative example, we focused on the analysis of the rat's frontal cortex ensemble dynamics during a decision-making task. Results suggest that, in line with recent hypotheses, rather than internal noise, it is the deterministic trend which most likely underlies
Burgers' turbulence problem with linear or quadratic external potential
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Leonenko, N.N.
2005-01-01
We consider solutions of Burgers' equation with linear or quadratic external potential and stationary random initial conditions of Ornstein-Uhlenbeck type. We study a class of limit laws that correspond to a scale renormalization of the solutions.......We consider solutions of Burgers' equation with linear or quadratic external potential and stationary random initial conditions of Ornstein-Uhlenbeck type. We study a class of limit laws that correspond to a scale renormalization of the solutions....
Random Young diagrams in a Rectangular Box
DEFF Research Database (Denmark)
Beltoft, Dan; Boutillier, Cédric; Enriquez, Nathanaël
We exhibit the limit shape of random Young diagrams having a distribution proportional to the exponential of their area, and confined in a rectangular box. The Ornstein-Uhlenbeck bridge arises from the fluctuations around the limit shape.......We exhibit the limit shape of random Young diagrams having a distribution proportional to the exponential of their area, and confined in a rectangular box. The Ornstein-Uhlenbeck bridge arises from the fluctuations around the limit shape....
Assessing the extent of non-stationary biases in GCMs
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2017-06-01
General circulation models (GCMs) are the main tools for estimating changes in the climate for the future. The imperfect representation of climate models introduces biases in the simulations that need to be corrected prior to their use for impact assessments. Bias correction methods generally assume that the bias calculated over the historical period does not change and can be applied to the future. This study investigates this assumption by considering the extent and nature of bias non-stationarity using 20th century precipitation and temperature simulations from six CMIP5 GCMs across Australia. Four statistics (mean, standard deviation, 10th and 90th quantiles) in monthly and seasonal biases are obtained for three different time window lengths (10, 25 and 33 years) to examine the properties of bias over time. This approach is repeated for two different phases of the Interdecadal Pacific Oscillation (IPO), which is known to have strong influences on the Australian climate. It is found that bias non-stationarity at decadal timescales is indeed an issue over some of Australia for some GCMs. When considering interdecadal variability there are significant difference in the bias between positive and negative phases of the IPO. Regional analyses confirmed these findings with the largest differences seen on the east coast of Australia, where IPO impacts tend to be the strongest. The nature of the bias non-stationarity found in this study suggests that it will be difficult to modify existing bias correction approaches to account for non-stationary biases. A more practical approach for impact assessments that use bias correction maybe to use a selection of GCMs where the assumption of bias non-stationarity holds.
Climate Informed Low Flow Frequency Analysis Using Nonstationary Modeling
Liu, D.; Guo, S.; Lian, Y.
2014-12-01
Stationarity is often assumed for frequency analysis of low flows in water resources management and planning. However, many studies have shown that flow characteristics, particularly the frequency spectrum of extreme hydrologic events,were modified by climate change and human activities and the conventional frequency analysis without considering the non-stationary characteristics may lead to costly design. The analysis presented in this paper was based on the more than 100 years of daily flow data from the Yichang gaging station 44 kilometers downstream of the Three Gorges Dam. The Mann-Kendall trend test under the scaling hypothesis showed that the annual low flows had significant monotonic trend, whereas an abrupt change point was identified in 1936 by the Pettitt test. The climate informed low flow frequency analysis and the divided and combined method are employed to account for the impacts from related climate variables and the nonstationarities in annual low flows. Without prior knowledge of the probability density function for the gaging station, six distribution functions including the Generalized Extreme Values (GEV), Pearson Type III, Gumbel, Gamma, Lognormal, and Weibull distributions have been tested to find the best fit, in which the local likelihood method is used to estimate the parameters. Analyses show that GEV had the best fit for the observed low flows. This study has also shown that the climate informed low flow frequency analysis is able to exploit the link between climate indices and low flows, which would account for the dynamic feature for reservoir management and provide more accurate and reliable designs for infrastructure and water supply.
Designing and operating infrastructure for nonstationary flood risk management
Doss-Gollin, J.; Farnham, D. J.; Lall, U.
2017-12-01
Climate exhibits organized low-frequency and regime-like variability at multiple time scales, causing the risk associated with climate extremes such as floods and droughts to vary in time. Despite broad recognition of this nonstationarity, there has been little theoretical development of ideas for the design and operation of infrastructure considering the regime structure of such changes and their potential predictability. We use paleo streamflow reconstructions to illustrate an approach to the design and operation of infrastructure to address nonstationary flood and drought risk. Specifically, we consider the tradeoff between flood control and conservation storage, and develop design and operation principles for allocating these storage volumes considering both a m-year project planning period and a n-year historical sampling record. As n increases, the potential uncertainty in probabilistic estimates of the return periods associated with the T-year extreme event decreases. As the duration m of the future operation period decreases, the uncertainty associated with the occurrence of the T-year event also increases. Finally, given the quasi-periodic nature of the system it may be possible to offer probabilistic predictions of the conditions in the m-year future period, especially if m is small. In the context of such predictions, one can consider that a m-year prediction may have lower bias, but higher variance, than would be associated with using a stationary estimate from the preceding n years. This bias-variance trade-off, and the potential for considering risk management for multiple values of m, provides an interesting system design challenge. We use wavelet-based simulation models in a Bayesian framework to estimate these biases and uncertainty distributions and devise a risk-optimized decision rule for the allocation of flood and conservation storage. The associated theoretical development also provides a methodology for the sizing of storage for new
International Nuclear Information System (INIS)
Man'ko, V.I.; Markov, M.A.
1984-01-01
This chapter considers the process of creation of particles with maximally big masses (maximons, intermediate bosons) in the nonstationary Universe within the framework of neutral and charged scalar field theory. The conclusions of the matter creation model for real particles (resonances) and hypothetical particles (maximons, friedmons, intermediate bosons) are analyzed. It is determined that if the mechanism of maximon's creation exists, then these particles must be stable. The maximons could be the final states of decaying black holes. A possible mechanism of cosmic ray creation as a result of ''vacuum'' generation of known unstable particles is discussed. The limits upon the mass and the life time of intermediate bosons are calculated. It is demonstrated that the creation of masses greater than 10 GeV, and with life times less than 10- 24 sec and quantity of elementary particles greater than 100 are in contradiction with the particle creation mechanism and the experimental mass density in the Universe. The formalism of the examined method and its vacuum properties are discussed in an appendix
International Nuclear Information System (INIS)
Feng, Ke; Wang, KeSheng; Zhang, Mian; Ni, Qing; Zuo, Ming J
2017-01-01
The planetary gearbox, due to its unique mechanical structures, is an important rotating machine for transmission systems. Its engineering applications are often in non-stationary operational conditions, such as helicopters, wind energy systems, etc. The unique physical structures and working conditions make the vibrations measured from planetary gearboxes exhibit a complex time-varying modulation and therefore yield complicated spectral structures. As a result, traditional signal processing methods, such as Fourier analysis, and the selection of characteristic fault frequencies for diagnosis face serious challenges. To overcome this drawback, this paper proposes a signal selection scheme for fault-emphasized diagnostics based upon two order tracking techniques. The basic procedures for the proposed scheme are as follows. (1) Computed order tracking is applied to reveal the order contents and identify the order(s) of interest. (2) Vold–Kalman filter order tracking is used to extract the order(s) of interest—these filtered order(s) constitute the so-called selected vibrations. (3) Time domain statistic indicators are applied to the selected vibrations for faulty information-emphasized diagnostics. The proposed scheme is explained and demonstrated in a signal simulation model and experimental studies and the method proves to be effective for planetary gearbox fault diagnosis. (paper)
International Nuclear Information System (INIS)
Lin, S.; Li, Y.; Liu, C.; Wang, H.; Zhang, N.; Cui, W.; Neuber, A.
2015-01-01
This paper presents a statistical theory for the initial onset of multipactor breakdown in coaxial transmission lines, taking both the nonuniform electric field and random electron emission velocity into account. A general numerical method is first developed to construct the joint probability density function based on the approximate equation of the electron trajectory. The nonstationary dynamics of the multipactor process on both surfaces of coaxial lines are modelled based on the probability of various impacts and their corresponding secondary emission. The resonant assumption of the classical theory on the independent double-sided and single-sided impacts is replaced by the consideration of their interaction. As a result, the time evolutions of the electron population for exponential growth and absorption on both inner and outer conductor, in response to the applied voltage above and below the multipactor breakdown level, are obtained to investigate the exact mechanism of multipactor discharge in coaxial lines. Furthermore, the multipactor threshold predictions of the presented model are compared with experimental results using measured secondary emission yield of the tested samples which shows reasonable agreement. Finally, the detailed impact scenario reveals that single-surface multipactor is more likely to occur with a higher outer to inner conductor radius ratio
Liu, Xin; Wang, Hongkai; Yan, Zhuangzhi
2016-11-01
Dynamic fluorescence molecular tomography (FMT) plays an important role in drug delivery research. However, the majority of current reconstruction methods focus on solving the stationary FMT problems. If the stationary reconstruction methods are applied to the time-varying fluorescence measurements, the reconstructed results may suffer from a high level of artifacts. In addition, based on the stationary methods, only one tomographic image can be obtained after scanning one circle projection data. As a result, the movement of fluorophore in imaged object may not be detected due to the relative long data acquisition time (typically >1 min). In this paper, we apply extended kalman filter (EKF) technique to solve the non-stationary fluorescence tomography problem. Especially, to improve the EKF reconstruction performance, the generalized inverse of kalman gain is calculated by a second-order iterative method. The numerical simulation, phantom, and in vivo experiments are performed to evaluate the performance of the method. The experimental results indicate that by using the proposed EKF-based second-order iterative (EKF-SOI) method, we cannot only clearly resolve the time-varying distributions of fluorophore within imaged object, but also greatly improve the reconstruction time resolution (~2.5 sec/frame) which makes it possible to detect the movement of fluorophore during the imaging processes.
Detection of Partial Demagnetization Fault in PMSMs Operating under Nonstationary Conditions
DEFF Research Database (Denmark)
Wang, Chao; Delgado Prieto, Miguel; Romeral, Luis
2016-01-01
Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold-Kalman F......Demagnetization fault detection of in-service Permanent Magnet Synchronous Machines (PMSMs) is a challenging task because most PMSMs operate under nonstationary circumstances in industrial applications. A novel approach based on tracking characteristic orders of stator current using Vold......-Kalman Filter is proposed to detect the partial demagnetization fault in PMSMs running at nonstationary conditions. Amplitude of envelope of the fault characteristic orders is used as fault indictor. Experimental results verify the superiority of the proposed method on partial demagnetization online fault...... detection of PMSMs under various speed and load conditions....
Directory of Open Access Journals (Sweden)
Xiang Zeng
2016-06-01
Full Text Available Abstract We prove some almost sure central limit theorems for the maxima of strongly dependent nonstationary Gaussian vector sequences under some mild conditions. The results extend the ASCLT to nonstationary Gaussian vector sequences and give substantial improvements for the weight sequence obtained by Lin et al. (Comput. Math. Appl. 62(2:635-640, 2011.
Veremey, N. E.; Dovgalyuk, Yu. A.; Zatevakhin, M. A.; Ignatyev, A. A.; Morozov, V. N.
2014-04-01
Numerical nonstationary three-dimensional model of a convective cloud with parameterized description of microphysical processes with allowance for the electrization processes is considered. The results of numerical modeling of the cloud evolution for the specified atmospheric conditions are presented. The spatio-temporal distribution of the main cloud characteristics including the volume charge density and the electric field is obtained. The calculation results show that the electric structure of the cloud is different at its various life stages, i.e., it varies from unipolar to dipolar and then to tripolar. This conclusion is in fair agreement with the field studies.
Energy Technology Data Exchange (ETDEWEB)
Ruiz, Jordi-Roger Riba [EUETII, Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya, Placa del Rei 15, 08700 Igualada, Barcelona (Spain); Garcia Espinosa, Antonio [Dept. d' Enginyeria Electrica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain); Romeral, Luis; Cusido, Jordi [Dept. d' Enginyeria Electronica, Universitat Politecnica de Catalunya C/Colom 1, 08222 Terrassa (Spain)
2010-10-15
Permanent magnet synchronous motors (PMSMs) are applied in high performance positioning and variable speed applications because of their enhanced features with respect to other AC motor types. Fault detection and diagnosis of electrical motors for critical applications is an active field of research. However, much research remains to be done in the field of PMSM demagnetization faults, especially when running under non-stationary conditions. This paper presents a time-frequency method specifically focused to detect and diagnose demagnetization faults in PMSMs running under non-stationary speed conditions, based on the Hilbert Huang transform. The effectiveness of the proposed method is proven by means of experimental results. (author)
International Nuclear Information System (INIS)
Lobashev, A.A.; Mostepanenko, V.M.
1993-01-01
Heisenberg formalism is developed for creation-annihilation operators of quantum fields propagating in nonstationary external fields. Quantum fields with spin 0,1/2, 1 are considered in the presence of such external fields as electromagnetic, scalar and the field of nonstationary dielectric properties of nonlinear medium. Elliptic operator parametrically depending on time is constructed. In Heisenberg representation field variables are decomposed over eigenfunction of this operator. The relation between Heisenberg creation-annihilation operators and the operators obtained in the frame of diagonalization of Hamiltonian with Bogoliubov transformations is set up
International Nuclear Information System (INIS)
Hartwig, J. T.; Stokman, J. V.
2013-01-01
We realize an extended version of the trigonometric Cherednik algebra as affine Dunkl operators involving Heaviside functions. We use the quadratic Casimir element of the extended trigonometric Cherednik algebra to define an explicit nonstationary Schrödinger equation with delta-potential. We use coordinate Bethe ansatz methods to construct solutions of the nonstationary Schrödinger equation in terms of generalized Bethe wave functions. It is shown that the generalized Bethe wave functions satisfy affine difference Knizhnik-Zamolodchikov equations as functions of the momenta. The relation to the vector valued root system analogs of the quantum Bose gas on the circle with delta-function interactions is indicated.
International Nuclear Information System (INIS)
Savchenko, E.V.; Khyzhniy, I.V.; Uyutov, S.A.; Gumenchuk, G.B.; Ponomarev, A.N.; Bondybey, V.E.; Beyer, M.K.
2010-01-01
The formation of excimers (Xe 2 H) * in solid Xe doped with molecular hydrogen under electron beam is studied using the original two-stage technique of nonstationary (NS) cathodoluminescence (CL) in combination with the current activation spectroscopy method - thermally stimulated exoelectron emission (TSEE). Charged species were generated using a high-density electron beam. The species produced were then probed with a low density beam on gradual sample heating. The near UV emission of the (Xe 2 H) * was used to monitor the neutralization process. It is found that the temperature behavior of the NS CL band of (Xe 2 H) * clearly correlates with the yield of TSEE measured after identical pre-irradiation of the sample. The fingerprints of the thermally stimulated detrapping of electrons - 'internal electron emission' in the spectrum of NS CL point to the essential role of neutralization reaction in the stability of the proton solvated by rare-gas atoms.
A Non-Stationary 1981–2012 AVHRR NDVI3g Time Series
Directory of Open Access Journals (Sweden)
Jorge E. Pinzon
2014-07-01
Full Text Available The NDVI3g time series is an improved 8-km normalized difference vegetation index (NDVI data set produced from Advanced Very High Resolution Radiometer (AVHRR instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of ± 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
A Non-Stationary 1981-2012 AVHRR NDVI(sub 3g) Time Series
Pinzon, Jorge E.; Tucker, Compton J.
2014-01-01
The NDVI(sub 3g) time series is an improved 8-km normalized difference vegetation index (NDVI) data set produced from Advanced Very High Resolution Radiometer (AVHRR) instruments that extends from 1981 to the present. The AVHRR instruments have flown or are flying on fourteen polar-orbiting meteorological satellites operated by the National Oceanic and Atmospheric Administration (NOAA) and are currently flying on two European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) polar-orbiting meteorological satellites, MetOp-A and MetOp-B. This long AVHRR record is comprised of data from two different sensors: the AVHRR/2 instrument that spans July 1981 to November 2000 and the AVHRR/3 instrument that continues these measurements from November 2000 to the present. The main difficulty in processing AVHRR NDVI data is to properly deal with limitations of the AVHRR instruments. Complicating among-instrument AVHRR inter-calibration of channels one and two is the dual gain introduced in late 2000 on the AVHRR/3 instruments for both these channels. We have processed NDVI data derived from the Sea-Viewing Wide Field-of-view Sensor (SeaWiFS) from 1997 to 2010 to overcome among-instrument AVHRR calibration difficulties. We use Bayesian methods with high quality well-calibrated SeaWiFS NDVI data for deriving AVHRR NDVI calibration parameters. Evaluation of the uncertainties of our resulting NDVI values gives an error of plus or minus 0.005 NDVI units for our 1981 to present data set that is independent of time within our AVHRR NDVI continuum and has resulted in a non-stationary climate data set.
Non-stationary covariance function modelling in 2D least-squares collocation
Darbeheshti, N.; Featherstone, W. E.
2009-06-01
Standard least-squares collocation (LSC) assumes 2D stationarity and 3D isotropy, and relies on a covariance function to account for spatial dependence in the observed data. However, the assumption that the spatial dependence is constant throughout the region of interest may sometimes be violated. Assuming a stationary covariance structure can result in over-smoothing of, e.g., the gravity field in mountains and under-smoothing in great plains. We introduce the kernel convolution method from spatial statistics for non-stationary covariance structures, and demonstrate its advantage for dealing with non-stationarity in geodetic data. We then compared stationary and non- stationary covariance functions in 2D LSC to the empirical example of gravity anomaly interpolation near the Darling Fault, Western Australia, where the field is anisotropic and non-stationary. The results with non-stationary covariance functions are better than standard LSC in terms of formal errors and cross-validation against data not used in the interpolation, demonstrating that the use of non-stationary covariance functions can improve upon standard (stationary) LSC.
Tracking of Nonstationary Noise Based on Data-Driven Recursive Noise Power Estimation
Erkelens, J.S.; Heusdens, R.
2008-01-01
This paper considers estimation of the noise spectral variance from speech signals contaminated by highly nonstationary noise sources. The method can accurately track fast changes in noise power level (up to about 10 dB/s). In each time frame, for each frequency bin, the noise variance estimate is
Optimal inventory policies with non-stationary supply disruptions and advance supply information
Atasoy, B.; Güllü, R.; Tan, T.
2012-01-01
We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages – and hence supply disruption to (some of) her customers
Optimal inventory policies with non-stationary supply disruptions and advance supply information
Atasoy, B.; Güllü, R.; Tan, T.
2011-01-01
We consider the production/inventory problem of a manufacturer (or a retailer) under non-stationary and stochastic supply availability. Although supply availability is uncertain, the supplier would be able to predict her near future shortages -and hence supply disruption to (some of) her customers-
Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.
2018-01-01
Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.
Production planning of a perishable product with lead time and non-stationary demand
Pauls-Worm, K.G.J.; Haijema, R.; Hendrix, E.M.T.; Rossi, R.; Vorst, van der J.G.A.J.
2012-01-01
We study a production planning problem for a perishable product with a fixed lifetime, under a service-level constraint. The product has a non-stationary stochastic demand. Food supply chains of fresh products like cheese and several crop products, are characterised by long lead times due to
Shi, Yingzhong; Chung, Fu-Lai; Wang, Shitong
2015-09-01
Recently, a time-adaptive support vector machine (TA-SVM) is proposed for handling nonstationary datasets. While attractive performance has been reported and the new classifier is distinctive in simultaneously solving several SVM subclassifiers locally and globally by using an elegant SVM formulation in an alternative kernel space, the coupling of subclassifiers brings in the computation of matrix inversion, thus resulting to suffer from high computational burden in large nonstationary dataset applications. To overcome this shortcoming, an improved TA-SVM (ITA-SVM) is proposed using a common vector shared by all the SVM subclassifiers involved. ITA-SVM not only keeps an SVM formulation, but also avoids the computation of matrix inversion. Thus, we can realize its fast version, that is, improved time-adaptive core vector machine (ITA-CVM) for large nonstationary datasets by using the CVM technique. ITA-CVM has the merit of asymptotic linear time complexity for large nonstationary datasets as well as inherits the advantage of TA-SVM. The effectiveness of the proposed classifiers ITA-SVM and ITA-CVM is also experimentally confirmed.
Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary 13C metabolic flux analysis (INST...
International Nuclear Information System (INIS)
Barry, J.M.; Pollard, J.P.
1986-11-01
A FORTRAN subroutine MLTGRD is provided to solve efficiently the large systems of linear equations arising from a five-point finite difference discretisation of some elliptic partial differential equations. MLTGRD is a multigrid algorithm which provides multiplicative correction to iterative solution estimates from successively reduced systems of linear equations. It uses the method of implicit non-stationary iteration for all grid levels
A flag-up algorithm and test for nonstationary customer-specific product graphs
DEFF Research Database (Denmark)
Fenger, Morten H. J.; Scholderer, Joachim
period. The results show that the test is clearly able to identify customers with evolving behavior, and that it can easily be deployed as part of a CRM system. It enables companies with loyalty programs to focus on nonstationary customers, i.e. customers who may represent opportunities for cross...
Boaretto, B. R. R.; Budzinski, R. C.; Prado, T. L.; Kurths, J.; Lopes, S. R.
2018-05-01
It is known that neural networks under small-world topology can present anomalous synchronization and nonstationary behavior for weak coupling regimes. Here, we propose methods to suppress the anomalous synchronization and also to diminish the nonstationary behavior occurring in weakly coupled neural network under small-world topology. We consider a network of 2000 thermally sensitive identical neurons, based on the model of Hodgkin-Huxley in a small-world topology, with the probability of adding non local connection equal to p = 0 . 001. Based on experimental protocols to suppress anomalous synchronization, as well as nonstationary behavior of the neural network dynamics, we make use of (i) external stimulus (pulsed current); (ii) biologic parameters changing (neuron membrane conductance changes); and (iii) body temperature changes. Quantification analysis to evaluate phase synchronization makes use of the Kuramoto's order parameter, while recurrence quantification analysis, particularly the determinism, computed over the easily accessible mean field of network, the local field potential (LFP), is used to evaluate nonstationary states. We show that the methods proposed can control the anomalous synchronization and nonstationarity occurring for weak coupling parameter without any effect on the individual neuron dynamics, neither in the expected asymptotic synchronized states occurring for large values of the coupling parameter.
A survey of techniques applied to non-stationary waveforms in electrical power systems
Rodrigues, R.P.; Silveira, P.M.; Ribeiro, P.F.
2010-01-01
The well-known and ever-present time-varying and non-stationary nature of waveforms in power systems requires a comprehensive and precise analytical basis that needs to be incorporated in the system studies and analyses. This time-varying behavior is due to continuous changes in system
Performance of a written radiation protection inspection of nonstationary gamma radiography users
International Nuclear Information System (INIS)
Hoehne, M.
1986-01-01
A questionare has been developed for controlling users of nonstationary gamma radiography devices. It is aimed at obtaining information about the weak points according to radiation protection and to give guidance in performing such controls by the respective radiation protection officers. The questionare is included
Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility
DEFF Research Database (Denmark)
Cavaliere, Guiseppe; Rahbæk, Anders; Taylor, A.M. Robert
Many key macro-economic and financial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...
Testing for Co-integration in Vector Autoregressions with Non-Stationary Volatility
DEFF Research Database (Denmark)
Cavaliere, Giuseppe; Rahbek, Anders Christian; Taylor, A. M. Robert
Many key macro-economic and …nancial variables are characterised by permanent changes in unconditional volatility. In this paper we analyse vector autoregressions with non-stationary (unconditional) volatility of a very general form, which includes single and multiple volatility breaks as special...
Magnetization of a warm plasma by the nonstationary ponderomotive force of an electromagnetic wave
International Nuclear Information System (INIS)
Shukla, Nitin; Shukla, P. K.; Stenflo, L.
2009-01-01
It is shown that magnetic fields can be generated in a warm plasma by the nonstationary ponderomotive force of a large-amplitude electromagnetic wave. In the present Brief Report, we derive simple and explicit results that can be useful for understanding the origin of the magnetic fields that are produced in intense laser-plasma interaction experiments.
Effect of non-stationary climate on infectious gastroenteritis transmission in Japan
Onozuka, Daisuke
2014-06-01
Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Infectious gastroenteritis cases were non-stationary and significantly associated with the IOD and ENSO (Multivariate ENSO Index [MEI], Niño 1 + 2, Niño 3, Niño 4, and Niño 3.4) for a period of approximately 1 to 2 years. This association was non-stationary and appeared to have a major influence on the synchrony of infectious gastroenteritis transmission. Our results suggest that non-stationary patterns of association between global climate factors and incidence of infectious gastroenteritis should be considered when developing early warning systems for epidemics of infectious gastroenteritis.
Non-stationary dynamics of climate variability in synchronous influenza epidemics in Japan
Onozuka, Daisuke; Hagihara, Akihito
2015-09-01
Seasonal variation in the incidence of influenza is widely assumed. However, few studies have examined non-stationary relationships between global climate factors and influenza epidemics. We examined the monthly incidence of influenza in Fukuoka, Japan, from 2000 to 2012 using cross-wavelet coherency analysis to assess the patterns of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). The monthly incidence of influenza showed cycles of 1 year with the IOD and 2 years with ENSO indices (Multivariate, Niño 4, and Niño 3.4). These associations were non-stationary and appeared to have major influences on the synchrony of influenza epidemics. Our study provides quantitative evidence that non-stationary associations have major influences on synchrony between the monthly incidence of influenza and the dynamics of the IOD and ENSO. Our results call for the consideration of non-stationary patterns of association between influenza cases and climatic factors in early warning systems.
Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.
2014-01-01
We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at
Inventory control for a perishable product with non-stationary demand and service level constraints
Pauls-Worm, K.G.J.; Hendrix, E.M.T.; Haijema, R.; Vorst, van der J.G.A.J.
2013-01-01
We study the practical production planning problem of a food producer facing a non-stationary erratic demand for a perishable product with a fixed life time. In meeting the uncertain demand, the food producer uses a FIFO issuing policy. The food producer aims at meeting a certain service level at
On the Oracle Property of the Adaptive LASSO in Stationary and Nonstationary Autoregressions
DEFF Research Database (Denmark)
Kock, Anders Bredahl
We show that the Adaptive LASSO is oracle efficient in stationary and non-stationary autoregressions. This means that it estimates parameters consistently, selects the correct sparsity pattern, and estimates the coefficients belonging to the relevant variables at the same asymptotic efficiency...
Double-Wavelet Approach to Studying the Modulation Properties of Nonstationary Multimode Dynamics
DEFF Research Database (Denmark)
Sosnovtseva, Olga; Mosekilde, Erik; Pavlov, A.N.
2005-01-01
On the basis of double-wavelet analysis, the paper proposes a method to study interactions in the form of frequency and amplitude modulation in nonstationary multimode data series. Special emphasis is given to the problem of quantifying the strength of modulation for a fast signal by a coexisting...
Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site
Directory of Open Access Journals (Sweden)
Xuhui He
2017-09-01
Full Text Available The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.
Measurement of Non-Stationary Characteristics of a Landfall Typhoon at the Jiangyin Bridge Site.
He, Xuhui; Qin, Hongxi; Tao, Tianyou; Liu, Wenshuo; Wang, Hao
2017-09-22
The wind-sensitive long-span suspension bridge is a vital element in land transportation. Understanding the wind characteristics at the bridge site is thus of great significance to the wind- resistant analysis of such a flexible structure. In this study, a strong wind event from a landfall typhoon called Soudelor recorded at the Jiangyin Bridge site with the anemometer is taken as the research object. As inherent time-varying trends are frequently captured in typhoon events, the wind characteristics of Soudelor are analyzed in a non-stationary perspective. The time-varying mean is first extracted with the wavelet-based self-adaptive method. Then, the non-stationary turbulent wind characteristics, e.g.; turbulence intensity, gust factor, turbulence integral scale, and power spectral density, are investigated and compared with the results from the stationary analysis. The comparison highlights the importance of non-stationary considerations of typhoon events, and a transition from stationarity to non-stationarity for the analysis of wind effects. The analytical results could help enrich the database of non-stationary wind characteristics, and are expected to provide references for the wind-resistant analysis of engineering structures in similar areas.
System identification through nonstationary data using Time-Frequency Blind Source Separation
Guo, Yanlin; Kareem, Ahsan
2016-06-01
Classical output-only system identification (SI) methods are based on the assumption of stationarity of the system response. However, measured response of buildings and bridges is usually non-stationary due to strong winds (e.g. typhoon, and thunder storm etc.), earthquakes and time-varying vehicle motions. Accordingly, the response data may have time-varying frequency contents and/or overlapping of modal frequencies due to non-stationary colored excitation. This renders traditional methods problematic for modal separation and identification. To address these challenges, a new SI technique based on Time-Frequency Blind Source Separation (TFBSS) is proposed. By selectively utilizing "effective" information in local regions of the time-frequency plane, where only one mode contributes to energy, the proposed technique can successfully identify mode shapes and recover modal responses from the non-stationary response where the traditional SI methods often encounter difficulties. This technique can also handle response with closely spaced modes which is a well-known challenge for the identification of large-scale structures. Based on the separated modal responses, frequency and damping can be easily identified using SI methods based on a single degree of freedom (SDOF) system. In addition to the exclusive advantage of handling non-stationary data and closely spaced modes, the proposed technique also benefits from the absence of the end effects and low sensitivity to noise in modal separation. The efficacy of the proposed technique is demonstrated using several simulation based studies, and compared to the popular Second-Order Blind Identification (SOBI) scheme. It is also noted that even some non-stationary response data can be analyzed by the stationary method SOBI. This paper also delineates non-stationary cases where SOBI and the proposed scheme perform comparably and highlights cases where the proposed approach is more advantageous. Finally, the performance of the
Global sea surface temperature (SST) anomalies can affect terrestrial precipitation via ocean-atmosphere interaction known as climate teleconnection. Non-stationary and non-linear characteristics of the ocean-atmosphere system make the identification of the teleconnection signals...
Active visual search in non-stationary scenes: coping with temporal variability and uncertainty
Ušćumlić, Marija; Blankertz, Benjamin
2016-02-01
Objective. State-of-the-art experiments for studying neural processes underlying visual cognition often constrain sensory inputs (e.g., static images) and our behavior (e.g., fixed eye-gaze, long eye fixations), isolating or simplifying the interaction of neural processes. Motivated by the non-stationarity of our natural visual environment, we investigated the electroencephalography (EEG) correlates of visual recognition while participants overtly performed visual search in non-stationary scenes. We hypothesized that visual effects (such as those typically used in human-computer interfaces) may increase temporal uncertainty (with reference to fixation onset) of cognition-related EEG activity in an active search task and therefore require novel techniques for single-trial detection. Approach. We addressed fixation-related EEG activity in an active search task with respect to stimulus-appearance styles and dynamics. Alongside popping-up stimuli, our experimental study embraces two composite appearance styles based on fading-in, enlarging, and motion effects. Additionally, we explored whether the knowledge obtained in the pop-up experimental setting can be exploited to boost the EEG-based intention-decoding performance when facing transitional changes of visual content. Main results. The results confirmed our initial hypothesis that the dynamic of visual content can increase temporal uncertainty of the cognition-related EEG activity in active search with respect to fixation onset. This temporal uncertainty challenges the pivotal aim to keep the decoding performance constant irrespective of visual effects. Importantly, the proposed approach for EEG decoding based on knowledge transfer between the different experimental settings gave a promising performance. Significance. Our study demonstrates that the non-stationarity of visual scenes is an important factor in the evolution of cognitive processes, as well as in the dynamic of ocular behavior (i.e., dwell time and
International Nuclear Information System (INIS)
Mikhin, V.I.; Matukhin, N.M.
2000-01-01
The approach to generalization of the non-stationary heat exchange data for the central zones of the nuclear reactor fuel assemblies and the approximate thermal-model-testing criteria are proposed. The fuel assemblies of fast and water-cooled reactors with different fuel compositions have been investigated. The reason of the non-stationary heat exchange is the fuel-energy-release time dependence. (author)
Evaluation of the Methods for Response Analysis under Non-Stationary Excitation
Directory of Open Access Journals (Sweden)
R.S. Jangid
1999-01-01
Full Text Available Response of structures to non-stationary ground motion can be obtained either by the evolutionary spectral analysis or by the Markov approach. In certain conditions, a quasi-stationary analysis can also be performed. The first two methods of analysis are difficult to apply for complex situations such as problems involving soil-structure interaction, non-classical damping and primary-secondary structure interaction. The quasi-stationary analysis, on the other hand, provides an easier solution procedure for such cases. Here-in, the effectiveness of the quasi-stationary analysis is examined with the help of the analysis of a single degree-of-freedom (SDOF system under a set of parametric variations. For this purpose, responses of the SDOF system to uniformly modulated non-stationary random ground excitation are obtained by the three methods and they are compared. In addition, the relative computational efforts for different methods are also investigated.
Detection of Unusual Events and Trends in Complex Non-Stationary Data Streams
International Nuclear Information System (INIS)
Perez, Rafael B.; Protopopescu, Vladimir A.; Worley, Brian Addison; Perez, Cristina
2006-01-01
The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for a host of different applications, ranging from nuclear power plant and electric grid operation to internet traffic and implementation of non-proliferation protocols. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden intermittent events inside non-stationary signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method
A Novel Simulator of Nonstationary Random MIMO Channels in Rayleigh Fading Scenarios
Directory of Open Access Journals (Sweden)
Qiuming Zhu
2016-01-01
Full Text Available For simulations of nonstationary multiple-input multiple-output (MIMO Rayleigh fading channels in time-variant scattering environments, a novel channel simulator is proposed based on the superposition of chirp signals. This new method has the advantages of low complexity and implementation simplicity as the sum of sinusoids (SOS method. In order to reproduce realistic time varying statistics for dynamic channels, an efficient parameter computation method is also proposed for updating the frequency parameters of employed chirp signals. Simulation results indicate that the proposed simulator is effective in generating nonstationary MIMO channels with close approximation of the time-variant statistical characteristics in accordance with the expected theoretical counterparts.
Non-stationary dynamics in the bouncing ball: A wavelet perspective
Energy Technology Data Exchange (ETDEWEB)
Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in [Department of Physical Sciences, Indian Institute of Science Education and Research (IISER) Kolkata, Mohanpur 741246 (India); Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in [Plasma Physics Division, Saha Institute of Nuclear Physics (SINP), Sector 1, Block-AF, Bidhannagar, Kolkata 700064 (India)
2014-12-01
The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.
Stationary and non-stationary extreme value modeling of extreme temperature in Malaysia
Hasan, Husna; Salleh, Nur Hanim Mohd; Kassim, Suraiya
2014-09-01
Extreme annual temperature of eighteen stations in Malaysia is fitted to the Generalized Extreme Value distribution. Stationary and non-stationary models with trend are considered for each station and the Likelihood Ratio test is used to determine the best-fitting model. Results show that three out of eighteen stations i.e. Bayan Lepas, Labuan and Subang favor a model which is linear in the location parameter. A hierarchical cluster analysis is employed to investigate the existence of similar behavior among the stations. Three distinct clusters are found in which one of them consists of the stations that favor the non-stationary model. T-year estimated return levels of the extreme temperature are provided based on the chosen models.
Elastic shells of revolution under nonstationary thermal loading using ring finite elements
International Nuclear Information System (INIS)
Yao Zhenhan
1986-01-01
The report deals with the analysis of elastic shells of revolution under nonstationary thermal loading using ring finite elements. First, a ring element for moderately thick shells is derived which should also be employed for thin shells when either higher Fourier components of the displacements, or deflection patterns with very steep gradients occur. Then, a ring element for the analysis of heat conduction in shells of revolution is derived, and algorithms for the numerical solution of linear stationary, nonlinear stationary, as well as linear nonstationary problems are presented. Finally, a ring element for the coupled thermoelastic analysis of shells of revolution is developed, and an algorithm for the solution of weakly coupled problems is given. (orig.) [de
A regional and nonstationary model for partial duration series of extreme rainfall
DEFF Research Database (Denmark)
Gregersen, Ida Bülow; Madsen, Henrik; Rosbjerg, Dan
2017-01-01
as the explanatory variables in the regional and temporal domain, respectively. Further analysis of partial duration series with nonstationary and regional thresholds shows that the mean exceedances also exhibit a significant variation in space and time for some rainfall durations, while the shape parameter is found...... of extreme rainfall. The framework is built on a partial duration series approach with a nonstationary, regional threshold value. The model is based on generalized linear regression solved by generalized estimation equations. It allows a spatial correlation between the stations in the network and accounts...... furthermore for variable observation periods at each station and in each year. Marginal regional and temporal regression models solved by generalized least squares are used to validate and discuss the results of the full spatiotemporal model. The model is applied on data from a large Danish rain gauge network...
Numerical Estimation Method for the NonStationary Thrust of Pulsejet Ejector Nozzle
Directory of Open Access Journals (Sweden)
A. Yu. Mikushkin
2016-01-01
Full Text Available The article considers a calculation method for the non-stationary thrust of pulsejet ejector nozzle that is based on detonation combustion of gaseous fuel.To determine initial distributions of the thermodynamic parameters inside the detonation tube was carried out a rapid analysis based on x-t-diagrams of motion of glowing combustion products. For this purpose, the section with transparent walls was connected to the outlet of the tube to register the movement of products of combustion.Based on obtained images and gas-dynamic and thermodynamic equations the velocity distribution of the combustion products, its density, pressure and temperature required for numerical analysis were calculated. The world literature presents data on distribution of parameters, however they are given only for direct initiation of detonation at the closed end and for chemically "frozen" gas composition. The article presents the interpolation methods of parameters measured at the temperatures of 2500-2800K.Estimation of the thermodynamic parameters is based on the Chapman-Jouguet theory that the speed of the combustion products directly behind the detonation wave front with respect to the wave front is equal to the speed of sound of these products at a given point. The method of minimizing enthalpy of the final thermodynamic state was used to calculate the equilibrium parameters. Thus, a software package «IVTANTHERMO», which is a database of thermodynamic properties of many individual substances in a wide temperature range, was used.An integral thrust was numerically calculated according to the ejector nozzle surface. We solved the Navier-Stokes equations using the finite-difference Roe scheme of the second order. The combustion products were considered both as an inert mixture with "frozen" composition and as a mixture in chemical equilibrium with the changing temperature. The comparison with experimental results was made.The above method can be used for rapid
ENSO's non-stationary and non-Gaussian character: the role of climate shifts
Boucharel, J.; Dewitte, B.; Garel, B.; Du Penhoat, Y.
2009-07-01
El Niño Southern Oscillation (ENSO) is the dominant mode of climate variability in the Pacific, having socio-economic impacts on surrounding regions. ENSO exhibits significant modulation on decadal to inter-decadal time scales which is related to changes in its characteristics (onset, amplitude, frequency, propagation, and predictability). Some of these characteristics tend to be overlooked in ENSO studies, such as its asymmetry (the number and amplitude of warm and cold events are not equal) and the deviation of its statistics from those of the Gaussian distribution. These properties could be related to the ability of the current generation of coupled models to predict ENSO and its modulation. Here, ENSO's non-Gaussian nature and asymmetry are diagnosed from in situ data and a variety of models (from intermediate complexity models to full-physics coupled general circulation models (CGCMs)) using robust statistical tools initially designed for financial mathematics studies. In particular α-stable laws are used as theoretical background material to measure (and quantify) the non-Gaussian character of ENSO time series and to estimate the skill of ``naïve'' statistical models in producing deviation from Gaussian laws and asymmetry. The former are based on non-stationary processes dominated by abrupt changes in mean state and empirical variance. It is shown that the α-stable character of ENSO may result from the presence of climate shifts in the time series. Also, cool (warm) periods are associated with ENSO statistics having a stronger (weaker) tendency towards Gaussianity and lower (greater) asymmetry. This supports the hypothesis of ENSO being rectified by changes in mean state through nonlinear processes. The relationship between changes in mean state and nonlinearity (skewness) is further investigated both in the Zebiak and Cane (1987)'s model and the models of the Intergovernmental Panel for Climate Change (IPCC). Whereas there is a clear relationship in all
International Nuclear Information System (INIS)
Kraus, B.; Tittel, W.; Gisin, N.; Nilsson, M.; Kroell, S.; Cirac, J. I.
2006-01-01
We propose a method for efficient storage and recall of arbitrary nonstationary light fields, such as, for instance, single photon time-bin qubits or intense fields, in optically dense atomic ensembles. Our approach to quantum memory is based on controlled, reversible, inhomogeneous broadening and relies on a hidden time-reversal symmetry of the optical Bloch equations describing the propagation of the light field. We briefly discuss experimental realizations of our proposal
On the dynamics of non-stationary binary stellar system with non-isotropic mass flow
International Nuclear Information System (INIS)
Bekov, A.A.; Bejsekov, A.N.; Aldibaeva, L.T.
2006-01-01
The motion of test body in the external gravitational field of the binary stellar systems with slowly variable some physical parameters of radiating components is considered on the base of restricted nonstationary photo-gravitational three and two bodies problem with non-isotropic mass flow. The family of polar and coplanar solutions are obtained. The solutions give the possibility of the dynamical and structure interpretation of binary young evolving stars and galaxies. (author)
Nonstationary behavior in a delayed feedback traveling wave tube folded waveguide oscillator
International Nuclear Information System (INIS)
Ryskin, N.M.; Titov, V.N.; Han, S.T.; So, J.K.; Jang, K.H.; Kang, Y.B.; Park, G.S.
2004-01-01
Folded waveguide traveling-wave tubes (FW TWT) are among the most promising candidates for powerful compact amplifiers and oscillators in millimeter and submillimeter wave bands. In this paper, the nonstationary behavior of a FW TWT oscillator with delayed feedback is investigated. Starting conditions of the oscillations are derived analytically. Results of numerical simulation of single-frequency, self-modulation (multifrequency) and chaotic generation regimes are presented. Mode competition phenomena, multistability and hysteresis are discussed
2016-03-01
each IDF curve and subsequently used to force a calibrated and validated precipitation - runoff model. Probability-based, risk-informed hydrologic...ERDC/CHL CHETN-X-2 March 2016 Approved for public release; distribution is unlimited. Bayesian Inference of Nonstationary Precipitation Intensity...based means by which to develop local precipitation Intensity-Duration-Frequency (IDF) curves using historical rainfall time series data collected for
Effect of non-stationary climate on infectious gastroenteritis transmission in Japan
Onozuka, Daisuke
2014-01-01
Local weather factors are widely considered to influence the transmission of infectious gastroenteritis. Few studies, however, have examined the non-stationary relationships between global climatic factors and transmission of infectious gastroenteritis. We analyzed monthly data for cases of infectious gastroenteritis in Fukuoka, Japan from 2000 to 2012 using cross-wavelet coherency analysis to assess the pattern of associations between indices for the Indian Ocean Dipole (IOD) and El Niño Sou...
A Non-Stationary Approach for Estimating Future Hydroclimatic Extremes Using Monte-Carlo Simulation
Byun, K.; Hamlet, A. F.
2017-12-01
There is substantial evidence that observed hydrologic extremes (e.g. floods, extreme stormwater events, and low flows) are changing and that climate change will continue to alter the probability distributions of hydrologic extremes over time. These non-stationary risks imply that conventional approaches for designing hydrologic infrastructure (or making other climate-sensitive decisions) based on retrospective analysis and stationary statistics will become increasingly problematic through time. To develop a framework for assessing risks in a non-stationary environment our study develops a new approach using a super ensemble of simulated hydrologic extremes based on Monte Carlo (MC) methods. Specifically, using statistically downscaled future GCM projections from the CMIP5 archive (using the Hybrid Delta (HD) method), we extract daily precipitation (P) and temperature (T) at 1/16 degree resolution based on a group of moving 30-yr windows within a given design lifespan (e.g. 10, 25, 50-yr). Using these T and P scenarios we simulate daily streamflow using the Variable Infiltration Capacity (VIC) model for each year of the design lifespan and fit a Generalized Extreme Value (GEV) probability distribution to the simulated annual extremes. MC experiments are then used to construct a random series of 10,000 realizations of the design lifespan, estimating annual extremes using the estimated unique GEV parameters for each individual year of the design lifespan. Our preliminary results for two watersheds in Midwest show that there are considerable differences in the extreme values for a given percentile between conventional MC and non-stationary MC approach. Design standards based on our non-stationary approach are also directly dependent on the design lifespan of infrastructure, a sensitivity which is notably absent from conventional approaches based on retrospective analysis. The experimental approach can be applied to a wide range of hydroclimatic variables of interest.
Non-stationary Condition Monitoring of large diesel engines with the AEWATT toolbox
DEFF Research Database (Denmark)
Pontoppidan, Niels Henrik; Larsen, Jan; Sigurdsson, Sigurdur
2005-01-01
We are developing a specialized toolbox for non-stationary condition monitoring of large 2-stroke diesel engines based on acoustic emission measurements. The main contribution of this toolbox has so far been the utilization of adaptive linear models such as Principal and Independent Component Ana......, the inversion of those angular timing changes called “event alignment”, has allowed for condition monitoring across operation load settings, successfully enabling a single model to be used with realistic data under varying operational conditions-...
A risk-based approach to flood management decisions in a nonstationary world
Rosner, Ana; Vogel, Richard M.; Kirshen, Paul H.
2014-03-01
Traditional approaches to flood management in a nonstationary world begin with a null hypothesis test of "no trend" and its likelihood, with little or no attention given to the likelihood that we might ignore a trend if it really existed. Concluding a trend exists when it does not, or rejecting a trend when it exists are known as type I and type II errors, respectively. Decision-makers are poorly served by statistical and/or decision methods that do not carefully consider both over- and under-preparation errors, respectively. Similarly, little attention is given to how to integrate uncertainty in our ability to detect trends into a flood management decision context. We show how trend hypothesis test results can be combined with an adaptation's infrastructure costs and damages avoided to provide a rational decision approach in a nonstationary world. The criterion of expected regret is shown to be a useful metric that integrates the statistical, economic, and hydrological aspects of the flood management problem in a nonstationary world.
Nonstationary influence of El Niño on the synchronous dengue epidemics in Thailand.
Directory of Open Access Journals (Sweden)
Bernard Cazelles
2005-04-01
Full Text Available BACKGROUND: Several factors, including environmental and climatic factors, influence the transmission of vector-borne diseases. Nevertheless, the identification and relative importance of climatic factors for vector-borne diseases remain controversial. Dengue is the world's most important viral vector-borne disease, and the controversy about climatic effects also applies in this case. Here we address the role of climate variability in shaping the interannual pattern of dengue epidemics. METHODS AND FINDINGS: We have analysed monthly data for Thailand from 1983 to 1997 using wavelet approaches that can describe nonstationary phenomena and that also allow the quantification of nonstationary associations between time series. We report a strong association between monthly dengue incidence in Thailand and the dynamics of El Niño for the 2-3-y periodic mode. This association is nonstationary, seen only from 1986 to 1992, and appears to have a major influence on the synchrony of dengue epidemics in Thailand. CONCLUSION: The underlying mechanism for the synchronisation of dengue epidemics may resemble that of a pacemaker, in which intrinsic disease dynamics interact with climate variations driven by El Niño to propagate travelling waves of infection. When association with El Niño is strong in the 2-3-y periodic mode, one observes high synchrony of dengue epidemics over Thailand. When this association is absent, the seasonal dynamics become dominant and the synchrony initiated in Bangkok collapses.
Self-organising mixture autoregressive model for non-stationary time series modelling.
Ni, He; Yin, Hujun
2008-12-01
Modelling non-stationary time series has been a difficult task for both parametric and nonparametric methods. One promising solution is to combine the flexibility of nonparametric models with the simplicity of parametric models. In this paper, the self-organising mixture autoregressive (SOMAR) network is adopted as a such mixture model. It breaks time series into underlying segments and at the same time fits local linear regressive models to the clusters of segments. In such a way, a global non-stationary time series is represented by a dynamic set of local linear regressive models. Neural gas is used for a more flexible structure of the mixture model. Furthermore, a new similarity measure has been introduced in the self-organising network to better quantify the similarity of time series segments. The network can be used naturally in modelling and forecasting non-stationary time series. Experiments on artificial, benchmark time series (e.g. Mackey-Glass) and real-world data (e.g. numbers of sunspots and Forex rates) are presented and the results show that the proposed SOMAR network is effective and superior to other similar approaches.
Directory of Open Access Journals (Sweden)
Yin Yanshu
2017-12-01
Full Text Available In this paper, a location-based multiple point statistics method is developed to model a non-stationary reservoir. The proposed method characterizes the relationship between the sedimentary pattern and the deposit location using the relative central position distance function, which alleviates the requirement that the training image and the simulated grids have the same dimension. The weights in every direction of the distance function can be changed to characterize the reservoir heterogeneity in various directions. The local integral replacements of data events, structured random path, distance tolerance and multi-grid strategy are applied to reproduce the sedimentary patterns and obtain a more realistic result. This method is compared with the traditional Snesim method using a synthesized 3-D training image of Poyang Lake and a reservoir model of Shengli Oilfield in China. The results indicate that the new method can reproduce the non-stationary characteristics better than the traditional method and is more suitable for simulation of delta-front deposits. These results show that the new method is a powerful tool for modelling a reservoir with non-stationary characteristics.
A comparison of three approaches to non-stationary flood frequency analysis
Debele, S. E.; Strupczewski, W. G.; Bogdanowicz, E.
2017-08-01
Non-stationary flood frequency analysis (FFA) is applied to statistical analysis of seasonal flow maxima from Polish and Norwegian catchments. Three non-stationary estimation methods, namely, maximum likelihood (ML), two stage (WLS/TS) and GAMLSS (generalized additive model for location, scale and shape parameters), are compared in the context of capturing the effect of non-stationarity on the estimation of time-dependent moments and design quantiles. The use of a multimodel approach is recommended, to reduce the errors due to the model misspecification in the magnitude of quantiles. The results of calculations based on observed seasonal daily flow maxima and computer simulation experiments showed that GAMLSS gave the best results with respect to the relative bias and root mean square error in the estimates of trend in the standard deviation and the constant shape parameter, while WLS/TS provided better accuracy in the estimates of trend in the mean value. Within three compared methods the WLS/TS method is recommended to deal with non-stationarity in short time series. Some practical aspects of the GAMLSS package application are also presented. The detailed discussion of general issues related to consequences of climate change in the FFA is presented in the second part of the article entitled "Around and about an application of the GAMLSS package in non-stationary flood frequency analysis".
The Fourier decomposition method for nonlinear and non-stationary time series analysis.
Singh, Pushpendra; Joshi, Shiv Dutt; Patney, Rakesh Kumar; Saha, Kaushik
2017-03-01
for many decades, there has been a general perception in the literature that Fourier methods are not suitable for the analysis of nonlinear and non-stationary data. In this paper, we propose a novel and adaptive Fourier decomposition method (FDM), based on the Fourier theory, and demonstrate its efficacy for the analysis of nonlinear and non-stationary time series. The proposed FDM decomposes any data into a small number of 'Fourier intrinsic band functions' (FIBFs). The FDM presents a generalized Fourier expansion with variable amplitudes and variable frequencies of a time series by the Fourier method itself. We propose an idea of zero-phase filter bank-based multivariate FDM (MFDM), for the analysis of multivariate nonlinear and non-stationary time series, using the FDM. We also present an algorithm to obtain cut-off frequencies for MFDM. The proposed MFDM generates a finite number of band-limited multivariate FIBFs (MFIBFs). The MFDM preserves some intrinsic physical properties of the multivariate data, such as scale alignment, trend and instantaneous frequency. The proposed methods provide a time-frequency-energy (TFE) distribution that reveals the intrinsic structure of a data. Numerical computations and simulations have been carried out and comparison is made with the empirical mode decomposition algorithms.
New Non-Stationary Gradient Model of Heat-Mass-Electric Charge Transfer in Thin Porous Media
Directory of Open Access Journals (Sweden)
V. Rogankov
2017-10-01
Full Text Available The well-known complicated system of non-equilibrium balance equations for a continuous fluid (f medium needs the new non-Gibbsian model of f-phase to be applicable for description of the heterogeneous porous media (PMs. It should be supplemented by the respective coupled thermal and caloric equations of state (EOS developed specially for PMs to become adequate and solvable for the irreversible transport f-processes. The set of standard assumptions adopted by the linear (or quasi-linear non-equilibrium thermodynamics are based on the empirical gradient-caused correlations between flows and forces. It leads, in particular, to the oversimplified stationary solutions for PMs. The most questionable but typical modeling suppositions of the stationary gradient (SG theory are: 1 the assumption of incompressibility accepted, as a rule, for f-flows; 2 the ignorance of distinctions between the hydrophilic and hydrophobic influence of a porous matrix on the properties; 3 the omission of effects arising due to the concomitant phase intra-porous transitions between the neighboring f-fragments with the sharp differences in densities; 4 the use of exclusively Gibbsian (i.e. homogeneous and everywhere differentiable description of any f-phase in PM; 5 the very restrictive reduction of the mechanical velocity field to its specific potential form in the balance equation of f-motion as well as of the heat velocity field in the balance equation of internal energy; 6 the neglect of the new specific peculiarities arising due to the study of any non-equilibrium PM in the meso- and nano-scales of a finite-size macroscopic (N,V-system of discrete particles. This work is an attempt to develop the alternative non-stationary gradient (NSG model of real irreversible processes in PM. Another aim is to apply it without the above restrictions 1-6 to the description of f-flows through the obviously non-Gibbsian thin porous medium (TPM. We will suppose that it is composed by two
Forootan, Ehsan; Kusche, Jürgen
2016-04-01
Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i
Energy Technology Data Exchange (ETDEWEB)
Kaczmarczyk, S [School of Applied Sciences, University of Northampton, St. George' s Avenue, Northampton NN2 6JD (United Kingdom); Iwankiewicz, R [Institute of Mechanics and Ocean Engineering, Hamburg University of Technology, Eissendorfer Strasse 42 D-21073, Hamburg (Germany); Terumichi, Y, E-mail: stefan.kaczmarczyk@northampton.ac.u [Faculty of Science and Technology, Sophia University, 7-1 KIOI-CHO, CHIYODAKU, Tokyo, 102-8554 Japan (Japan)
2009-08-01
Moving slender elastic elements such as ropes, cables and belts are pivotal components of vertical transportation systems such as traction elevators. Their lengths vary within the host building structure during the elevator operation which results in the change of the mass and stiffness characteristics of the system. The structure of modern high-rise buildings is flexible and when subjected to loads due to strong winds and earthquakes it vibrates at low frequencies. The inertial load induced by the building motion excites the flexible components of the elevator system. The compensating ropes due to their lower tension are particularly affected and undergo large dynamic deformations. The paper focuses on the presentation of the non-stationary model of a building-compensating rope system and on the analysis to predict its dynamic response. The excitation mechanism is represented by a harmonic process and the results of computer simulations to predict transient resonance response are presented. The analysis of the simulation results leads to recommendations concerning the selection of the weight of the compensation assembly to minimize the effects of an adverse dynamic response of the system. The scenario when the excitation is represented as a narrow-band stochastic process with the state vector governed by stochastic equations is then discussed and the stochastic differential equations governing the second-order statistical moments of the state vector are developed.
Adapting Bayes Network Structures to Non-stationary Domains
DEFF Research Database (Denmark)
Nielsen, Søren Holbech; Nielsen, Thomas Dyhre
2008-01-01
When an incremental structural learning method gradually modifies a Bayesian network (BN) structure to fit a sequential stream of observations, we call the process structural adaptation. Structural adaptation is useful when the learner is set to work in an unknown environment, where a BN is gradu...
Brune sections in the non-stationary case
Alpay, Daniel; Bolotnikov, Vladimir; Dewilde, Patrick; Dijksma, Aad
2002-01-01
Rational J-inner-valued functions which are J-inner with respect to the unit circle (J being a matrix which is both self-adjoint and unitary) play an important role in interpolation theory and are extensively utilized in signal processing for filtering purposes and in control for minimal sensitivity
A reversible transform for seismic data processing
International Nuclear Information System (INIS)
Burnett, William A; Ferguson, Robert J
2011-01-01
We use the nonstationary equivalent of the Fourier shift theorem to derive a general one-dimensional integral transform for the application and removal of certain seismic data processing steps. This transform comes from the observation that many seismic data processing steps can be viewed as nonstationary shifts. The continuous form of the transform is exactly reversible, and the discrete form provides a general framework for unitary and pseudounitary imaging operators. Any processing step which can be viewed as a nonstationary shift in any domain is a special case of this transform. Nonstationary shifts generally produce coordinate distortions between input and output domains, and those that preserve amplitudes do not conserve the energy of the input signal. The nonstationary frequency distortions, time distortions and nonphysical energy changes inherent to such operations are predicted and quantified by this transform. Processing steps of this type are conventionally implemented using interpolation operators to map discrete data values between input and output coordinate frames. Although not explicitly derived to perform interpolation, the transform here assumes the Fourier basis to predict values of the input signal between sampling locations. We demonstrate how interpolants commonly used in seismic data processing and imaging approximate the proposed method. We find that our transform is equivalent to the conventional sinc interpolant with no truncation. Once the transform is developed, we demonstrate its numerical implementation by matrix–vector multiplication. As an example, we use our transform to apply and remove normal moveout
Scattering matrix approach to non-stationary quantum transport
Moskalets, Michael V
2012-01-01
The aim of this book is to introduce the basic elements of the scattering matrix approach to transport phenomena in dynamical quantum systems of non-interacting electrons. This approach admits a physically clear and transparent description of transport processes in dynamical mesoscopic systems promising basic elements of solid-state devices for quantum information processing. One of the key effects, the quantum pump effect, is considered in detail. In addition, the theory for a recently implemented new dynamical source - injecting electrons with time delay much larger than the electron coherence time - is offered. This theory provides a simple description of quantum circuits with such a single-particle source and shows in an unambiguous way that the tunability inherent to the dynamical systems leads to a number of unexpected but fundamental effects.
International Nuclear Information System (INIS)
Jiang, Yu; Li, Zhixiong; Zhang, Chao; Peng, Z; Hu, Chao
2016-01-01
This work aims to detect rolling bearing cracks using a variational approach. An original method that appropriately incorporates bi-dimensional variational mode decomposition (BVMD) into discriminant diffusion maps (DDM) is proposed to analyze the nonstationary vibration signals recorded from the cracked rolling bearings in coal cutters. The advantage of this variational decomposition based diffusion map (VDDM) method in comparison to the current DDM is that the intrinsic vibration mode of the crack can be filtered into a limited bandwidth in the frequency domain with an estimated central frequency, thus discarding the interference signal components in the vibration signals and significantly improving the crack detection performance. In addition, the VDDM is able to simultaneously process two-channel sensor signals to reduce information leakage. Experimental validation using rolling bearing crack vibration signals demonstrates that the VDDM separated the raw signals into four intrinsic modes, including one roller vibration mode, one roller cage vibration mode, one inner race vibration mode, and one outer race vibration mode. Hence, reliable fault features were extracted from the outer race vibration mode, and satisfactory crack identification performance was achieved. The comparison between the proposed VDDM and existing approaches indicated that the VDDM method was more efficient and reliable for crack detection in coal cutter rolling bearings. As an effective catalyst for rolling bearing crack detection, this newly proposed method is useful for practical applications. (paper)
Gustof, P.; Hornik, A.
2016-09-01
In the paper, numeric calculations of thermal stresses of the piston in a turbocharged Diesel engine in the initial phase of its work were carried out based on experimental studies and the data resulting from them. The calculations were made using a geometrical model of the piston in a five-cylinder turbocharged Diesel engine with a capacity of about 2300 cm3, with a direct fuel injection to the combustion chamber and a power rating of 85 kW. In order to determine the thermal stress, application of own mathematical models of the heat flow in characteristic surfaces of the piston was required to show real processes occurring on the surface of the analysed component. The calculations were performed using a Geostar COSMOS/M program module. A three-dimensional geometric model of the piston was created in this program based on a real component, in order to enable the calculations and analysis of thermal stresses during non-stationary heat flow. Modelling of the thermal stresses of the piston for the engine speed n=4250 min-1 and engine load λ=1.69 was carried out.
Effects of non-stationary noise on consonant identification
DEFF Research Database (Denmark)
Zaar, Johannes; Kowalewski, Borys; Dau, Torsten
2018-01-01
recognition scores were inversely related to the amount of simultaneous masking. However, even with minimum simultaneous masking, a substantial loss of consonant recognition was observed at low SNRs, suggesting a forward masking effect. The model, which employs adaptive processes in the front end, accounted...... in such conditions. Normal-hearing listeners were presented with 15 Danish CVs in 5-Hz interrupted noise at SNRs of −20, −10, 0, and 10 dB. Five different CV onset times with respect to the noise bursts were considered, differing in the amount of induced simultaneous and forward masking. As expected, the consonant...
Sampling rare events in nonequilibrium and nonstationary systems.
Berryman, Joshua T; Schilling, Tanja
2010-12-28
Although many computational methods for rare event sampling exist, this type of calculation is not usually practical for general nonequilibrium conditions, with macroscopically irreversible dynamics and away from both stationary and metastable states. A novel method for calculating the time-series of the probability of a rare event is presented which is designed for these conditions. The method is validated for the cases of the Glauber-Ising model under time-varying shear flow, the Kawasaki-Ising model after a quench into the region between nucleation dominated and spinodal decomposition dominated phase change dynamics, and the parallel open asymmetric exclusion process. The method requires a subdivision of the phase space of the system: it is benchmarked and found to scale well for increasingly fine subdivisions, meaning that it can be applied without detailed foreknowledge of the physically important reaction pathways.
Non-stationary heat transfer in gels applied to biotehnology
Directory of Open Access Journals (Sweden)
Pokusaev Boris
2017-01-01
Full Text Available Unsteady heat transfer in agarose gels of various concentrations was studied in order to make a breakthrough in the technology of 3-D additive bioprinting. Data on the kinetics of the phase transformation was obtained using spectroscopy as a function of temperature during the formation of agarose hydrogel. The dynamics of aging was investigated for gels of different densities. The time dependence of the structural changes was obtained. Particular attention was paid to the changes in the structure of the gel due to the processes of evaporation of the liquid during the gel formation and during long-term storage. Experiments were performed to determine the dynamics of the temperature fields simultaneously with heat flux measurements during the formation of agarose gels from different initial concentrations. A technique based on experimental data for the computations of the thermophysical coefficients of agarose gels was developed.
Light scattering under conditions of nonstationary electromagnetically induced transparency
International Nuclear Information System (INIS)
Larionov, N V; Sokolov, I M
2007-01-01
The propagation of probe radiation pulses in ultracold atomic ensembles is studied theoretically under conditions of electromagnetically induced transparency. The pulse 'stopping' process is considered which takes place upon nonadiabatic switching off and subsequent switching on the control field. We analysed the formation of an inverted recovered probe radiation pulse, i.e. the pulse propagating in the direction opposite to the propagation direction before the pulse stopping. Based on this analysis, a scheme is proposed for lidar probing atomic or molecular clouds in which the probe pulse penetrates into a cloud over the specified depth, while information on the cloud state is obtained from the parameters of the inverted pulse. Calculations are performed for an ensemble of 87 Rb atoms. (fifth seminar in memory of d.n. klyshko)
Reduction of Non-stationary Noise using a Non-negative Latent Variable Decomposition
DEFF Research Database (Denmark)
Schmidt, Mikkel Nørgaard; Larsen, Jan
2008-01-01
We present a method for suppression of non-stationary noise in single channel recordings of speech. The method is based on a non-negative latent variable decomposition model for the speech and noise signals, learned directly from a noisy mixture. In non-speech regions an over complete basis...... is learned for the noise that is then used to jointly estimate the speech and the noise from the mixture. We compare the method to the classical spectral subtraction approach, where the noise spectrum is estimated as the average over non-speech frames. The proposed method significantly outperforms...
Energy Technology Data Exchange (ETDEWEB)
Lan, X.G. [Southwest Jiaotong University, Quantum Optoelectronics Laboratory, Chengdu (China); China West Normal University, Institute of Theoretical Physics, Nanchong (China); Jiang, Q.Q. [China West Normal University, Institute of Theoretical Physics, Nanchong (China); Wei, L.F. [Southwest Jiaotong University, Quantum Optoelectronics Laboratory, Chengdu (China); Sun Yat-Sen University, State Key Laboratory of Optoelectronic Materials and Technologies, School of Physics and Engineering, Guangzhou (China)
2012-04-15
We apply the Damour-Ruffini-Sannan method to study the Hawking radiations of scalar and Dirac particles in non-stationary Kerr black holes under different tortoise coordinate transformations. We found that all the relevant Hawking radiation spectra show still the blackbody ones, while the Hawking temperatures are strongly related to the used tortoise coordinate transformations. The properties of these dependences are discussed analytically and numerically. Our results imply that proper selections of tortoise coordinate transformations should be important in the studies of Hawking radiations and the correct selection would be given by the experimental observations in the future. (orig.)
Heat transfer and hydrodynamics of nonstationary dispersed-film flow in complex shape channels
International Nuclear Information System (INIS)
Nigmatulin, B.I.; Klebanov, L.A.; Kroshilin, A.E.; Kroshilin, V.E.
1980-01-01
The mathematical model has been used to investigate the dispersed-film regime of a liquid flow and condition for the appearance of heat transfer crisis. One-dimensional motion equations are used for each component of the mixture. The model developed is used to describe the hydrodynamics and the crisis of heat transfer in rod bundles and round tubes under stationary and nonstationary conditions. The account of a separate flow of a liquid film and a vapourdrop nucleus permits to describe the main regularities of a dispersed film flow. A good agreement of calculation and experimental results is obtained [ru
Noise Reduction for Nonlinear Nonstationary Time Series Data using Averaging Intrinsic Mode Function
Directory of Open Access Journals (Sweden)
Christofer Toumazou
2013-07-01
Full Text Available A novel noise filtering algorithm based on averaging Intrinsic Mode Function (aIMF, which is a derivation of Empirical Mode Decomposition (EMD, is proposed to remove white-Gaussian noise of foreign currency exchange rates that are nonlinear nonstationary times series signals. Noise patterns with different amplitudes and frequencies were randomly mixed into the five exchange rates. A number of filters, namely; Extended Kalman Filter (EKF, Wavelet Transform (WT, Particle Filter (PF and the averaging Intrinsic Mode Function (aIMF algorithm were used to compare filtering and smoothing performance. The aIMF algorithm demonstrated high noise reduction among the performance of these filters.
Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion
DEFF Research Database (Denmark)
Skjærbæk, P. S.; Kirkegaard, Poul Henning; Fouskitakis, G. N.
1997-01-01
This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modeling and simulation of this behaviour...... by an epicentral distance of 16 km and measured during the 1979 Imperial Valley earthquake in California (U .S .A.). The results of the study indicate that while all three approaches can successfully predict near-source ground motions, the Neural Network based one gives somewhat poorer simulation results....
Non-Stationary Modelling and Simulation of Near-Source Earthquake Ground Motion
DEFF Research Database (Denmark)
Skjærbæk, P. S.; Kirkegaard, Poul Henning; Fouskitakis, G. N.
This paper is concerned with modelling and simulation of near-source earthquake ground motion. Recent studies have revealed that these motions show heavy non-stationary behaviour with very low frequencies dominating parts of the earthquake sequence. Modelling and simulation of this behaviour...... by an epicentral distance of 16 km and measured during the 1979 Imperial valley earthquake in California (USA). The results of the study indicate that while all three approaches can succesfully predict near-source ground motions, the Neural Network based one gives somewhat poorer simulation results....
Distributed Nonstationary Heat Model of Two-Channel Solar Air Heater
International Nuclear Information System (INIS)
Klychev, Sh. I.; Bakhramov, S. A.; Ismanzhanov, A. I.; Tashiev, N.N.
2011-01-01
An algorithm for a distributed nonstationary heat model of a solar air heater (SAH) with two operating channels is presented. The model makes it possible to determine how the coolant temperature changes with time along the solar air heater channel by considering its main thermal and ambient parameters, as well as variations in efficiency. Examples of calculations are presented. It is shown that the time within which the mean-day efficiency of the solar air heater becomes stable is significantly higher than the time within which the coolant temperature reaches stable values. The model can be used for investigation of the performances of solar water-heating collectors. (authors)
AUTOMATIC CONTROL OF PARAMETERS OF A NON-STATIONARY OBJECT WITH CROSS LINKS
Directory of Open Access Journals (Sweden)
A. Pavlov
2018-04-01
Full Text Available Many objects automatic control unsteady. This is manifested in the change of their parameters. Therefore, periodically adjust the required parameters of the controller. This work is usually carried out rarely. For a long time, regulators are working with is not the optimal settings. The consequence of this is the low quality of many industrial control systems. The solution problem is the use of robust controllers. ACS with traditional PI and PID controllers have a very limited range of normal operation modes due to the appearance of parametric disturbances due to changes in the characteristics of the automated unit and changes in the load on it. The situation is different when using in the architecture of artificial neural network controllers. It is known that when training a neural network, the adaptation procedure is often used. This makes it possible to greatly expand the area of normal operating modes of ACS with neural automatic regulators in comparison with traditional linear regulators. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional object, provided that when designing the ACS at the stage of its simulation in the model of the regulatory object model, an adequate simulation model of the executive device. It is also possible to significantly improve the quality of control (especially for a non-stationary multidimensional regulatory object model, an adequate simulation model of the executive device. Especially actual implementation of all these requirements in the application of electric actuators. This article fully complies with these requirements. This is what makes it possible to provide a guaranteed quality of control in non-stationary ACS with multidimensional objects and cross-links between control channels. The possibility of using a known hybrid automatic regulator to stabilize the parameters of a two-channel non-stationary object with two cross-linked. A
Damage of first wall materials in fusion reactors under nonstationary thermal effects
International Nuclear Information System (INIS)
Maslaev, S.A.; Platonov, Yu.M.; Pimenov, V.N.
1991-01-01
The temperature distribution in the first wall of a fusion reactor was calculated for nonstationary thermal effects of the type of plasma destruction or the flow of 'running electrons' taking into account the melting of the surface layer of the material. The thickness of the resultant damaged layer in which thermal stresses were higher than the tensile strength of the material is estimated. The results were obtained for corrosion-resisting steel, aluminium and vanadium. Flowing down of the molten layer of the material of the first wall is calculated. (author)
Analytic solution of boundary-value problems for nonstationary model kinetic equations
International Nuclear Information System (INIS)
Latyshev, A.V.; Yushkanov, A.A.
1993-01-01
A theory for constructing the solutions of boundary-value problems for non-stationary model kinetic equations is constructed. This theory was incorrectly presented equation, separation of the variables is used, this leading to a characteristic equation. Eigenfunctions are found in the space of generalized functions, and the eigenvalue spectrum is investigated. An existence and uniqueness theorem for the expansion of the Laplace transform of the solution with respect to the eigenfunctions is proved. The proof is constructive and gives explicit expressions for the expansion coefficients. An application to the Rayleigh problem is obtained, and the corresponding result of Cercignani is corrected
Kwasniok, Frank
2013-11-01
A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.
The role of initial values in nonstationary fractional time series models
DEFF Research Database (Denmark)
Johansen, Søren; Nielsen, Morten Ørregaard
We consider the nonstationary fractional model $\\Delta^{d}X_{t}=\\varepsilon _{t}$ with $\\varepsilon_{t}$ i.i.d.$(0,\\sigma^{2})$ and $d>1/2$. We derive an analytical expression for the main term of the asymptotic bias of the maximum likelihood estimator of $d$ conditional on initial values, and we...... discuss the role of the initial values for the bias. The results are partially extended to other fractional models, and three different applications of the theoretical results are given....
Non-stationary ionization in the low ionosphere by gravitational wave action
International Nuclear Information System (INIS)
Nikitin, M.A.; Kashchenko, N.M.
1977-01-01
Non-stationary effects in the lower ionosphere caused by gravitation waves are analyzed. Time dependences are obtained for extremum electron concentrations, which describe the dynamics of heterogeneous layer formation from the initially homogeneous distribution under the effect of gravitation waves. Diffusion of plasma and its complex composition are not taken into account. The problem is solved for two particular cases of low and high frequency gravitation waves impact on the ionosphere. Only in the former case electron concentration in the lower ionosphere deviates considerably from the equilibrium
Detection of unusual events and trends in complex non-stationary data streams
International Nuclear Information System (INIS)
Charlton-Perez, C.; Perez, R.B.; Protopopescu, V.; Worley, B.A.
2011-01-01
The search for unusual events and trends hidden in multi-component, nonlinear, non-stationary, noisy signals is extremely important for diverse applications, ranging from power plant operation to homeland security. In the context of this work, we define an unusual event as a local signal disturbance and a trend as a continuous carrier of information added to and different from the underlying baseline dynamics. The goal of this paper is to investigate the feasibility of detecting hidden events inside intermittent signal data sets corrupted by high levels of noise, by using the Hilbert-Huang empirical mode decomposition method.
Radio-Oxidation in Polyolefins: Non-Stationary Kinetic Conditions
International Nuclear Information System (INIS)
Dely, N.
2006-01-01
In the last fifty years, many authors have been interested in the radio-oxidation processes occurring in polymers. The polymer degradation under ionising radiations in presence of dioxygen is well described by a radical chemistry. The radio-oxidation process occurs in three steps: the first one is the production of radicals P degree by interaction between the polymer and the ionising radiations; then radicals P degree react spontaneously with O 2 solved in the polymer giving a peroxy radical POO degree which attacks the polymer forming a hydroperoxide POOH and a new radical P degree (propagation). The third step corresponds to the termination step, that is bimolecular reactions between radicals. It is generally assumed that the stationary state is rapidly reached and consequently that the oxidation induced during the built-up period of the radical concentration can be neglected. However, to our best knowledge, the temporal evolution of radical concentrations before reaching the steady state regime has never been studied in details. We recently performed a complete study of oxygen consumption under electron irradiation for an EPDM elastomer. An analysis, as function of dose rate and oxygen pressure, and assuming steady state conditions, allowed extracting all the kinetic constants. Starting for these experimental data, we calculated the build-up of the radical concentration by solving numerically the differential equations with help of the Minichem code. We conclude that, in fact, the oxidation induced during the built-up period is negligible. In this paper we show that [P degree] could present a quasi-stationary plateau before reaching its stationary level. Consequently, the full radical time evolution is essentially determined by two characteristic times for reaching the quasi and stationary levels and three concentrations: [P degree] and [POO degree] at the stationary level and [P degree] at the quasi-stationary plateau. We show that realistic approximations can
Stochastic calibration and learning in nonstationary hydroeconomic models
Maneta, M. P.; Howitt, R.
2014-05-01
Concern about water scarcity and adverse climate events over agricultural regions has motivated a number of efforts to develop operational integrated hydroeconomic models to guide adaptation and optimal use of water. Once calibrated, these models are used for water management and analysis assuming they remain valid under future conditions. In this paper, we present and demonstrate a methodology that permits the recursive calibration of economic models of agricultural production from noisy but frequently available data. We use a standard economic calibration approach, namely positive mathematical programming, integrated in a data assimilation algorithm based on the ensemble Kalman filter equations to identify the economic model parameters. A moving average kernel ensures that new and past information on agricultural activity are blended during the calibration process, avoiding loss of information and overcalibration for the conditions of a single year. A regularization constraint akin to the standard Tikhonov regularization is included in the filter to ensure its stability even in the presence of parameters with low sensitivity to observations. The results show that the implementation of the PMP methodology within a data assimilation framework based on the enKF equations is an effective method to calibrate models of agricultural production even with noisy information. The recursive nature of the method incorporates new information as an added value to the known previous observations of agricultural activity without the need to store historical information. The robustness of the method opens the door to the use of new remote sensing algorithms for operational water management.
Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates
DEFF Research Database (Denmark)
Han, Heejoon; Kristensen, Dennis
as captured by its long-memory parameter dx; in particular, we allow for both stationary and non-stationary covariates. We show that the QMLE'’s of the regression coefficients entering the volatility equation are consistent and normally distributed in large samples independently of the degree of persistence....... This implies that standard inferential tools, such as t-statistics, do not have to be adjusted to the level of persistence. On the other hand, the intercept in the volatility equation is not identifi…ed when the covariate is non-stationary which is akin to the results of Jensen and Rahbek (2004, Econometric...
Kozitskiy, Sergey
2018-05-01
Numerical simulation of nonstationary dissipative structures in 3D double-diffusive convection has been performed by using the previously derived system of complex Ginzburg-Landau type amplitude equations, valid in a neighborhood of Hopf bifurcation points. Simulation has shown that the state of spatiotemporal chaos develops in the system. It has the form of nonstationary structures that depend on the parameters of the system. The shape of structures does not depend on the initial conditions, and a limited number of spectral components participate in their formation.
An Integrated Real-Time Beamforming and Postfiltering System for Nonstationary Noise Environments
Directory of Open Access Journals (Sweden)
Gannot Sharon
2003-01-01
Full Text Available We present a novel approach for real-time multichannel speech enhancement in environments of nonstationary noise and time-varying acoustical transfer functions (ATFs. The proposed system integrates adaptive beamforming, ATF identification, soft signal detection, and multichannel postfiltering. The noise canceller branch of the beamformer and the ATF identification are adaptively updated online, based on hypothesis test results. The noise canceller is updated only during stationary noise frames, and the ATF identification is carried out only when desired source components have been detected. The hypothesis testing is based on the nonstationarity of the signals and the transient power ratio between the beamformer primary output and its reference noise signals. Following the beamforming and the hypothesis testing, estimates for the signal presence probability and for the noise power spectral density are derived. Subsequently, an optimal spectral gain function that minimizes the mean square error of the log-spectral amplitude (LSA is applied. Experimental results demonstrate the usefulness of the proposed system in nonstationary noise environments.
Non-stationary and relaxation phenomena in cavity-assisted quantum memories
Veselkova, N. G.; Sokolov, I. V.
2017-12-01
We investigate the non-stationary and relaxation phenomena in cavity-assisted quantum memories for light. As a storage medium we consider an ensemble of cold atoms with standard Lambda-scheme of working levels. Some theoretical aspects of the problem were treated previously by many authors, and recent experiments stimulate more deep insight into the ultimate ability and limitations of the device. Since quantum memories can be used not only for the storage of quantum information, but also for a substantial manipulation of ensembles of quantum states, the speed of such manipulation and hence the ability to write and retrieve the signals of relatively short duration becomes important. In our research we do not apply the so-called bad cavity limit, and consider the memory operation of the signals whose duration is not much larger than the cavity field lifetime, accounting also for the finite lifetime of atomic coherence. In our paper we present an effective approach that makes it possible to find the non-stationary amplitude and phase behavior of strong classical control field, that matches the desirable time profile of both the envelope and the phase of the retrieved quantized signal. The phase properties of the retrieved quantized signals are of importance for the detection and manipulation of squeezing, entanglement, etc by means of optical mixing and homodyning.
Quantum Radiation Properties of Dirac Particles in General Nonstationary Black Holes
Directory of Open Access Journals (Sweden)
Jia-Chen Hua
2014-01-01
Full Text Available Quantum radiation properties of Dirac particles in general nonstationary black holes in the general case are investigated by both using the method of generalized tortoise coordinate transformation and considering simultaneously the asymptotic behaviors of the first-order and second-order forms of Dirac equation near the event horizon. It is generally shown that the temperature and the shape of the event horizon of this kind of black holes depend on both the time and different angles. Further, we give a general expression of the new extra coupling effect in thermal radiation spectrum of Dirac particles which is absent from the thermal radiation spectrum of scalar particles. Also, we reveal a relationship that is ignored before between thermal radiation and nonthermal radiation in the case of scalar particles, which is that the chemical potential in thermal radiation spectrum is equal to the highest energy of the negative energy state of scalar particles in nonthermal radiation for general nonstationary black holes.
Directory of Open Access Journals (Sweden)
A. K. Nekrasov
2006-03-01
Full Text Available A general nonlinear theory for low-frequency electromagnetic field generation due to high-frequency nonuniform and nonstationary electromagnetic radiations in cold, uniform, multicomponent, dusty magnetoplasmas is developed. This theory permits us to consider the nonlinear action of all waves that can exist in such plasmas. The equations are derived for the dust grain velocities in the low-frequency nonlinear electric fields arising due to the presence of electromagnetic cyclotron waves travelling along the background magnetic field. The dust grains are considered to be magnetized as well as unmagnetized. Different regimes for the dust particle dynamics, depending on the spatio-temporal change of the wave amplitudes and plasma parameters, are discussed. It is shown that induced nonlinear electric fields can have both an electrostatic and electromagnetic nature. Conditions for maximum dust acceleration are found. The results obtained may be useful for understanding the possible mechanisms of dust grain dynamics in astrophysical, cosmic and laboratory plasmas under the action of nonuniform and nonstationary electromagnetic waves.
Dynamics of Inhomogeneous Shell Systems Under Non-Stationary Loading (Survey)
Lugovoi, P. Z.; Meish, V. F.
2017-09-01
Experimental works on the determination of dynamics of smooth and stiffened cylindrical shells contacting with a soil medium under various non-stationary loading are reviewed. The results of studying three-layer shells of revolution whose motion equations are obtained within the framework of the hypotheses of the Timoshenko geometrically nonlinear theory are stated. The numerical results for shells with a piecewise or discrete filler enable the analysis of estimation of the influence of geometrical and physical-mechanical parameters of structures on their dynamics and reveal new mechanical effects. Basing on the classical theory of shells and rods, the effect of the discrete arrangement of ribs and coefficients of the Winkler or Pasternak elastic foundation on the normal frequencies and modes of rectangular planar cylindrical and spherical shells is studied. The number and shape of dispersion curves for longitudinal harmonic waves in a stiffened cylindrical shell are determined. The equations of vibrations of ribbed shells of revolution on Winkler or Pasternak elastic foundation are obtained using the geometrically nonlinear theory and the Timoshenko hypotheses. On applying the integral-interpolational method, numerical algorithms are developed and the corresponding non-stationary problems are solved. The special attention is paid to the statement and solution of coupled problems on the dynamical interaction of cylindrical or spherical shells with the soil water-saturated medium of different structure.
A non-stationary cost-benefit based bivariate extreme flood estimation approach
Qi, Wei; Liu, Junguo
2018-02-01
Cost-benefit analysis and flood frequency analysis have been integrated into a comprehensive framework to estimate cost effective design values. However, previous cost-benefit based extreme flood estimation is based on stationary assumptions and analyze dependent flood variables separately. A Non-Stationary Cost-Benefit based bivariate design flood estimation (NSCOBE) approach is developed in this study to investigate influence of non-stationarities in both the dependence of flood variables and the marginal distributions on extreme flood estimation. The dependence is modeled utilizing copula functions. Previous design flood selection criteria are not suitable for NSCOBE since they ignore time changing dependence of flood variables. Therefore, a risk calculation approach is proposed based on non-stationarities in both marginal probability distributions and copula functions. A case study with 54-year observed data is utilized to illustrate the application of NSCOBE. Results show NSCOBE can effectively integrate non-stationarities in both copula functions and marginal distributions into cost-benefit based design flood estimation. It is also found that there is a trade-off between maximum probability of exceedance calculated from copula functions and marginal distributions. This study for the first time provides a new approach towards a better understanding of influence of non-stationarities in both copula functions and marginal distributions on extreme flood estimation, and could be beneficial to cost-benefit based non-stationary bivariate design flood estimation across the world.
Directory of Open Access Journals (Sweden)
P. Ribereau
2008-12-01
Full Text Available Since the pioneering work of Landwehr et al. (1979, Hosking et al. (1985 and their collaborators, the Probability Weighted Moments (PWM method has been very popular, simple and efficient to estimate the parameters of the Generalized Extreme Value (GEV distribution when modeling the distribution of maxima (e.g., annual maxima of precipitations in the Identically and Independently Distributed (IID context. When the IID assumption is not satisfied, a flexible alternative, the Maximum Likelihood Estimation (MLE approach offers an elegant way to handle non-stationarities by letting the GEV parameters to be time dependent. Despite its qualities, the MLE applied to the GEV distribution does not always provide accurate return level estimates, especially for small sample sizes or heavy tails. These drawbacks are particularly true in some non-stationary situations. To reduce these negative effects, we propose to extend the PWM method to a more general framework that enables us to model temporal covariates and provide accurate GEV-based return levels. Theoretical properties of our estimators are discussed. Small and moderate sample sizes simulations in a non-stationary context are analyzed and two brief applications to annual maxima of CO_{2} and seasonal maxima of cumulated daily precipitations are presented.
Climate variability and nonstationary dynamics of Mycoplasma pneumoniae pneumonia in Japan.
Onozuka, Daisuke; Chaves, Luis Fernando
2014-01-01
A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae) pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales. We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD) and El Niño Southern Oscillation (ENSO). Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1-2-year periodic mode in 2005-2007 and 2010-2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics. Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.
Climate variability and nonstationary dynamics of Mycoplasma pneumoniae pneumonia in Japan.
Directory of Open Access Journals (Sweden)
Daisuke Onozuka
Full Text Available BACKGROUND: A stationary association between climate factors and epidemics of Mycoplasma pneumoniae (M. pneumoniae pneumonia has been widely assumed. However, it is unclear whether elements of the local climate that are relevant to M. pneumoniae pneumonia transmission have stationary signatures of climate factors on their dynamics over different time scales. METHODS: We performed a cross-wavelet coherency analysis to assess the patterns of association between monthly M. pneumoniae cases in Fukuoka, Japan, from 2000 to 2012 and indices for the Indian Ocean Dipole (IOD and El Niño Southern Oscillation (ENSO. RESULTS: Monthly M. pneumoniae cases were strongly associated with the dynamics of both the IOD and ENSO for the 1-2-year periodic mode in 2005-2007 and 2010-2011. This association was non-stationary and appeared to have a major influence on the synchrony of M. pneumoniae epidemics. CONCLUSIONS: Our results call for the consideration of non-stationary, possibly non-linear, patterns of association between M. pneumoniae cases and climatic factors in early warning systems.
A review on prognostic techniques for non-stationary and non-linear rotating systems
Kan, Man Shan; Tan, Andy C. C.; Mathew, Joseph
2015-10-01
The field of prognostics has attracted significant interest from the research community in recent times. Prognostics enables the prediction of failures in machines resulting in benefits to plant operators such as shorter downtimes, higher operation reliability, reduced operations and maintenance cost, and more effective maintenance and logistics planning. Prognostic systems have been successfully deployed for the monitoring of relatively simple rotating machines. However, machines and associated systems today are increasingly complex. As such, there is an urgent need to develop prognostic techniques for such complex systems operating in the real world. This review paper focuses on prognostic techniques that can be applied to rotating machinery operating under non-linear and non-stationary conditions. The general concept of these techniques, the pros and cons of applying these methods, as well as their applications in the research field are discussed. Finally, the opportunities and challenges in implementing prognostic systems and developing effective techniques for monitoring machines operating under non-stationary and non-linear conditions are also discussed.
Probing Gamma-ray Emission of Geminga & Vela with Non-stationary Models
Directory of Open Access Journals (Sweden)
Yating Chai
2016-06-01
Full Text Available It is generally believed that the high energy emissions from isolated pulsars are emitted from relativistic electrons/positrons accelerated in outer magnetospheric accelerators (outergaps via a curvature radiation mechanism, which has a simple exponential cut-off spectrum. However, many gamma-ray pulsars detected by the Fermi LAT (Large Area Telescope cannot be fitted by simple exponential cut-off spectrum, and instead a sub-exponential is more appropriate. It is proposed that the realistic outergaps are non-stationary, and that the observed spectrum is a superposition of different stationary states that are controlled by the currents injected from the inner and outer boundaries. The Vela and Geminga pulsars have the largest fluxes among all targets observed, which allows us to carry out very detailed phase-resolved spectral analysis. We have divided the Vela and Geminga pulsars into 19 (the off pulse of Vela was not included and 33 phase bins, respectively. We find that most phase resolved spectra still cannot be fitted by a simple exponential spectrum: in fact, a sub-exponential spectrum is necessary. We conclude that non-stationary states exist even down to the very fine phase bins.
Trend analysis using non-stationary time series clustering based on the finite element method
Gorji Sefidmazgi, M.; Sayemuzzaman, M.; Homaifar, A.; Jha, M. K.; Liess, S.
2014-05-01
In order to analyze low-frequency variability of climate, it is useful to model the climatic time series with multiple linear trends and locate the times of significant changes. In this paper, we have used non-stationary time series clustering to find change points in the trends. Clustering in a multi-dimensional non-stationary time series is challenging, since the problem is mathematically ill-posed. Clustering based on the finite element method (FEM) is one of the methods that can analyze multidimensional time series. One important attribute of this method is that it is not dependent on any statistical assumption and does not need local stationarity in the time series. In this paper, it is shown how the FEM-clustering method can be used to locate change points in the trend of temperature time series from in situ observations. This method is applied to the temperature time series of North Carolina (NC) and the results represent region-specific climate variability despite higher frequency harmonics in climatic time series. Next, we investigated the relationship between the climatic indices with the clusters/trends detected based on this clustering method. It appears that the natural variability of climate change in NC during 1950-2009 can be explained mostly by AMO and solar activity.
Self-adaptive change detection in streaming data with non-stationary distribution
Zhang, Xiangliang
2010-01-01
Non-stationary distribution, in which the data distribution evolves over time, is a common issue in many application fields, e.g., intrusion detection and grid computing. Detecting the changes in massive streaming data with a non-stationary distribution helps to alarm the anomalies, to clean the noises, and to report the new patterns. In this paper, we employ a novel approach for detecting changes in streaming data with the purpose of improving the quality of modeling the data streams. Through observing the outliers, this approach of change detection uses a weighted standard deviation to monitor the evolution of the distribution of data streams. A cumulative statistical test, Page-Hinkley, is employed to collect the evidence of changes in distribution. The parameter used for reporting the changes is self-adaptively adjusted according to the distribution of data streams, rather than set by a fixed empirical value. The self-adaptability of the novel approach enhances the effectiveness of modeling data streams by timely catching the changes of distributions. We validated the approach on an online clustering framework with a benchmark KDDcup 1999 intrusion detection data set as well as with a real-world grid data set. The validation results demonstrate its better performance on achieving higher accuracy and lower percentage of outliers comparing to the other change detection approaches. © 2010 Springer-Verlag.
Maximum non-extensive entropy block bootstrap for non-stationary processes
Czech Academy of Sciences Publication Activity Database
Bergamelli, M.; Novotný, Jan; Urga, G.
2015-01-01
Roč. 91, 1/2 (2015), s. 115-139 ISSN 0001-771X R&D Projects: GA ČR(CZ) GA14-27047S Institutional support: RVO:67985998 Keywords : maximum entropy * bootstrap * Monte Carlo simulations Subject RIV: AH - Economics
Analyzing Developmental Processes on an Individual Level Using Nonstationary Time Series Modeling
Molenaar, Peter C. M.; Sinclair, Katerina O.; Rovine, Michael J.; Ram, Nilam; Corneal, Sherry E.
2009-01-01
Individuals change over time, often in complex ways. Generally, studies of change over time have combined individuals into groups for analysis, which is inappropriate in most, if not all, studies of development. The authors explain how to identify appropriate levels of analysis (individual vs. group) and demonstrate how to estimate changes in…
Czech Academy of Sciences Publication Activity Database
Poplová, Michaela; Sovka, P.; Cifra, Michal
2017-01-01
Roč. 12, č. 12 (2017), č. článku e0188622. E-ISSN 1932-6203 R&D Projects: GA ČR(CZ) GA13-29294S Grant - others:AV ČR(CZ) SAV-15-22 Program:Bilaterální spolupráce Institutional support: RVO:67985882 Keywords : Poisson distribution * Photons * Neutrophils Subject RIV: JB - Sensors, Measurment, Regulation OBOR OECD: Electrical and electronic engineering Impact factor: 2.806, year: 2016
Simulation of some nonstationary astrophysical processes in laser-produced-plasma experiments
International Nuclear Information System (INIS)
Antonov, V.M.; Zakharov, Yu.P.; Orishich, A.M.; Ponomarenko, A.G.; Posukh, V.G.
1985-01-01
Preliminary results and calibration are reported on the astrophysical plasma dynamics simulator. This apparatus creates a spherical plasma cloud by the irradiation of a perlon filament target from two radial opposite directions by pulses of highly ionized background plasma in a high-vacuum chamber with diameter of 1.2 m and length of 5 m. The spherical plasma cloud simulates the exploding peripheric part of a supernova, expanding into the interstellar medium. (author)
A Novel Method for Generating Non-Stationary Gaussian Processes for Use in Digital Radar Simulators
National Research Council Canada - National Science Library
Boehm, James A; Debroux, Patrick S
2007-01-01
This report presents a novel and simple way to determine the transient response of the output of any linear system, described in the s-domain by an nth order polynomial, subjected to white Gaussian noise...
Pincheira-Donoso, Daniel; Harvey, Lilly P; Ruta, Marcello
2015-08-07
Adaptive radiation theory posits that ecological opportunity promotes rapid proliferation of phylogenetic and ecological diversity. Given that adaptive radiation proceeds via occupation of available niche space in newly accessed ecological zones, theory predicts that: (i) evolutionary diversification follows an 'early-burst' process, i.e., it accelerates early in the history of a clade (when available niche space facilitates speciation), and subsequently slows down as niche space becomes saturated by new species; and (ii) phylogenetic branching is accompanied by diversification of ecologically relevant phenotypic traits among newly evolving species. Here, we employ macroevolutionary phylogenetic model-selection analyses to address these two predictions about evolutionary diversification using one of the most exceptionally species-rich and ecologically diverse lineages of living vertebrates, the South American lizard genus Liolaemus. Our phylogenetic analyses lend support to a density-dependent lineage diversification model. However, the lineage through-time diversification curve does not provide strong support for an early burst. In contrast, the evolution of phenotypic (body size) relative disparity is high, significantly different from a Brownian model during approximately the last 5 million years of Liolaemus evolution. Model-fitting analyses also reject the 'early-burst' model of phenotypic evolution, and instead favour stabilizing selection (Ornstein-Uhlenbeck, with three peaks identified) as the best model for body size diversification. Finally, diversification rates tend to increase with smaller body size. Liolaemus have diversified under a density-dependent process with slightly pronounced apparent episodic pulses of lineage accumulation, which are compatible with the expected episodic ecological opportunity created by gradual uplifts of the Andes over the last ~25My. We argue that ecological opportunity can be strong and a crucial driver of adaptive
Møller, Jonas B; Overgaard, Rune V; Madsen, Henrik; Hansen, Torben; Pedersen, Oluf; Ingwersen, Steen H
2010-02-01
Several articles have investigated stochastic differential equations (SDEs) in PK/PD models, but few have quantitatively investigated the benefits to predictive performance of models based on real data. Estimation of first phase insulin secretion which reflects beta-cell function using models of the OGTT is a difficult problem in need of further investigation. The present work aimed at investigating the power of SDEs to predict the first phase insulin secretion (AIR (0-8)) in the IVGTT based on parameters obtained from the minimal model of the OGTT, published by Breda et al. (Diabetes 50(1):150-158, 2001). In total 174 subjects underwent both an OGTT and a tolbutamide modified IVGTT. Estimation of parameters in the oral minimal model (OMM) was performed using the FOCE-method in NONMEM VI on insulin and C-peptide measurements. The suggested SDE models were based on a continuous AR(1) process, i.e. the Ornstein-Uhlenbeck process, and the extended Kalman filter was implemented in order to estimate the parameters of the models. Inclusion of the Ornstein-Uhlenbeck (OU) process caused improved description of the variation in the data as measured by the autocorrelation function (ACF) of one-step prediction errors. A main result was that application of SDE models improved the correlation between the individual first phase indexes obtained from OGTT and AIR (0-8) (r = 0.36 to r = 0.49 and r = 0.32 to r = 0.47 with C-peptide and insulin measurements, respectively). In addition to the increased correlation also the properties of the indexes obtained using the SDE models more correctly assessed the properties of the first phase indexes obtained from the IVGTT. In general it is concluded that the presented SDE approach not only caused autocorrelation of errors to decrease but also improved estimation of clinical measures obtained from the glucose tolerance tests. Since, the estimation time of extended models was not heavily increased compared to basic models, the applied method
International Nuclear Information System (INIS)
Keanini, R.G.
2011-01-01
Research highlights: → Systematic approach for physically probing nonlinear and random evolution problems. → Evolution of vortex sheets corresponds to evolution of an Ornstein-Uhlenbeck process. → Organization of near-molecular scale vorticity mediated by hydrodynamic modes. → Framework allows calculation of vorticity evolution within random strain fields. - Abstract: A framework which combines Green's function (GF) methods and techniques from the theory of stochastic processes is proposed for tackling nonlinear evolution problems. The framework, established by a series of easy-to-derive equivalences between Green's function and stochastic representative solutions of linear drift-diffusion problems, provides a flexible structure within which nonlinear evolution problems can be analyzed and physically probed. As a preliminary test bed, two canonical, nonlinear evolution problems - Burgers' equation and the nonlinear Schroedinger's equation - are first treated. In the first case, the framework provides a rigorous, probabilistic derivation of the well known Cole-Hopf ansatz. Likewise, in the second, the machinery allows systematic recovery of a known soliton solution. The framework is then applied to a fairly extensive exploration of physical features underlying evolution of randomly stretched and advected Burger's vortex sheets. Here, the governing vorticity equation corresponds to the Fokker-Planck equation of an Ornstein-Uhlenbeck process, a correspondence that motivates an investigation of sub-sheet vorticity evolution and organization. Under the assumption that weak hydrodynamic fluctuations organize disordered, near-molecular-scale, sub-sheet vorticity, it is shown that these modes consist of two weakly damped counter-propagating cross-sheet acoustic modes, a diffusive cross-sheet shear mode, and a diffusive cross-sheet entropy mode. Once a consistent picture of in-sheet vorticity evolution is established, a number of analytical results, describing the
International Nuclear Information System (INIS)
Pupko, V.Ya.
1978-01-01
The equation of nonstationary heat transfer caused by the appearance of a local pulse jump in the factor of heat transfer to a coolant is solved analytically for a cylindrical fuel element. The problem solution is generalized to a case of the periodically pulsating factor of heat transfer according to its value in an arbitrary point of the fuel element surface
Demaria, E. M.; Goodrich, D. C.; Keefer, T.
2017-12-01
Observed sub-daily precipitation intensities from contrasting hydroclimatic environments in the USA are used to evaluate temporal trends and to develop Intensity-Duration Frequency (IDF) curves under stationary and nonstationary climatic conditions. Analyses are based on observations from two United States Department of Agriculture (USDA)-Agricultural Research Service (ARS) experimental watersheds located in a semi-arid and a temperate environment. We use an Annual Maximum Series (AMS) and a Partial Duration Series (PDS) approach to identify temporal trends in maximum intensities for durations ranging from 5- to 1440-minutes. A Bayesian approach with Monte Carlo techniques is used to incorporate the effect of non-stationary climatic assumptions in the IDF curves. The results show increasing trends in observed AMS sub-daily intensities in both watersheds whereas trends in the PDS observations are mostly positive in the semi-arid site and a mix of positive and negative in the temperate site. Stationary climate assumptions lead to much lower estimated sub-daily intensities than those under non-stationary assumptions with larger absolute differences found for shorter durations and smaller return periods. The risk of failure (R) of a hydraulic structure is increased for non-stationary effects over those of stationary effects, with absolute differences of 25% for a 100-year return period (T) and a project life (n) of 100 years. The study highlights the importance of considering non-stationarity, due to natural variability or to climate change, in storm design.
Woźniak, M.; Smołka, M.; Cortes, Adriano Mauricio; Paszyński, M.; Schaefer, R.
2016-01-01
We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme
Lin, Weilu; Wang, Zejian; Huang, Mingzhi; Zhuang, Yingping; Zhang, Siliang
2018-06-01
The isotopically non-stationary 13C labelling experiments, as an emerging experimental technique, can estimate the intracellular fluxes of the cell culture under an isotopic transient period. However, to the best of our knowledge, the issue of the structural identifiability analysis of non-stationary isotope experiments is not well addressed in the literature. In this work, the local structural identifiability analysis for non-stationary cumomer balance equations is conducted based on the Taylor series approach. The numerical rank of the Jacobian matrices of the finite extended time derivatives of the measured fractions with respect to the free parameters is taken as the criterion. It turns out that only one single time point is necessary to achieve the structural identifiability analysis of the cascaded linear dynamic system of non-stationary isotope experiments. The equivalence between the local structural identifiability of the cascaded linear dynamic systems and the local optimum condition of the nonlinear least squares problem is elucidated in the work. Optimal measurements sets can then be determined for the metabolic network. Two simulated metabolic networks are adopted to demonstrate the utility of the proposed method. Copyright © 2018 Elsevier Inc. All rights reserved.
Identification of QRS complex in non-stationary electrocardiogram of sick infants.
Kota, S; Swisher, C B; Al-Shargabi, T; Andescavage, N; du Plessis, A; Govindan, R B
2017-08-01
Due to the high-frequency of routine interventions in an intensive care setting, electrocardiogram (ECG) recordings from sick infants are highly non-stationary, with recurrent changes in the baseline, alterations in the morphology of the waveform, and attenuations of the signal strength. Current methods lack reliability in identifying QRS complexes (a marker of individual cardiac cycles) in the non-stationary ECG. In the current study we address this problem by proposing a novel approach to QRS complex identification. Our approach employs lowpass filtering, half-wave rectification, and the use of instantaneous Hilbert phase to identify QRS complexes in the ECG. We demonstrate the application of this method using ECG recordings from eight preterm infants undergoing intensive care, as well as from 18 normal adult volunteers available via a public database. We compared our approach to the commonly used approaches including Pan and Tompkins (PT), gqrs, wavedet, and wqrs for identifying QRS complexes and then compared each with manually identified QRS complexes. For preterm infants, a comparison between the QRS complexes identified by our approach and those identified through manual annotations yielded sensitivity and positive predictive values of 99% and 99.91%, respectively. The comparison metrics for each method are as follows: PT (sensitivity: 84.49%, positive predictive value: 99.88%), gqrs (85.25%, 99.49%), wavedet (95.24%, 99.86%), and wqrs (96.99%, 96.55%). Thus, the sensitivity values of the four methods previously described, are lower than the sensitivity of the method we propose; however, the positive predictive values of these other approaches is comparable to those of our method, with the exception of the wqrs approach, which yielded a slightly lower value. For adult ECG, our approach yielded a sensitivity of 99.78%, whereas PT yielded 99.79%. The positive predictive value was 99.42% for both our approach as well as for PT. We propose a novel method for
Flood frequency analysis of historical flood data under stationary and non-stationary modelling
Machado, M. J.; Botero, B. A.; López, J.; Francés, F.; Díez-Herrero, A.; Benito, G.
2015-06-01
Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913-2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency
Project Lifespan-based Nonstationary Hydrologic Design Methods for Changing Environment
Xiong, L.
2017-12-01
Under changing environment, we must associate design floods with the design life period of projects to ensure the hydrologic design is really relevant to the operation of the hydrologic projects, because the design value for a given exceedance probability over the project life period would be significantly different from that over other time periods of the same length due to the nonstationarity of probability distributions. Several hydrologic design methods that take the design life period of projects into account have been proposed in recent years, i.e. the expected number of exceedances (ENE), design life level (DLL), equivalent reliability (ER), and average design life level (ADLL). Among the four methods to be compared, both the ENE and ER methods are return period-based methods, while DLL and ADLL are risk/reliability- based methods which estimate design values for given probability values of risk or reliability. However, the four methods can be unified together under a general framework through a relationship transforming the so-called representative reliability (RRE) into the return period, i.e. m=1/1(1-RRE), in which we compute the return period m using the representative reliability RRE.The results of nonstationary design quantiles and associated confidence intervals calculated by ENE, ER and ADLL were very similar, since ENE or ER was a special case or had a similar expression form with respect to ADLL. In particular, the design quantiles calculated by ENE and ADLL were the same when return period was equal to the length of the design life. In addition, DLL can yield similar design values if the relationship between DLL and ER/ADLL return periods is considered. Furthermore, ENE, ER and ADLL had good adaptability to either an increasing or decreasing situation, yielding not too large or too small design quantiles. This is important for applications of nonstationary hydrologic design methods in actual practice because of the concern of choosing the emerging
Aristizabal, F; Glavinovic, M I
2003-10-01
Tracking spectral changes of rapidly varying signals is a demanding task. In this study, we explore on Monte Carlo-simulated glutamate-activated AMPA patch and synaptic currents whether a wavelet analysis offers such a possibility. Unlike Fourier methods that determine only the frequency content of a signal, the wavelet analysis determines both the frequency and the time. This is owing to the nature of the basis functions, which are infinite for Fourier transforms (sines and cosines are infinite), but are finite for wavelet analysis (wavelets are localized waves). In agreement with previous reports, the frequency of the stationary patch current fluctuations is higher for larger currents, whereas the mean-variance plots are parabolic. The spectra of the current fluctuations and mean-variance plots are close to the theoretically predicted values. The median frequency of the synaptic and nonstationary patch currents is, however, time dependent, though at the peak of synaptic currents, the median frequency is insensitive to the number of glutamate molecules released. Such time dependence demonstrates that the "composite spectra" of the current fluctuations gathered over the whole duration of synaptic currents cannot be used to assess the mean open time or effective mean open time of AMPA channels. The current (patch or synaptic) versus median frequency plots show hysteresis. The median frequency is thus not a simple reflection of the overall receptor saturation levels and is greater during the rise phase for the same saturation level. The hysteresis is due to the higher occupancy of the doubly bound state during the rise phase and not due to the spatial spread of the saturation disk, which remains remarkably constant. Albeit time dependent, the variance of the synaptic and nonstationary patch currents can be accurately determined. Nevertheless the evaluation of the number of AMPA channels and their single current from the mean-variance plots of patch or synaptic
Directory of Open Access Journals (Sweden)
Abhinav Parihar
2018-04-01
Full Text Available Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2 based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT models for Ornstein-Uhlenbeck (OU process to include a
Stochastic Models for Laser Propagation in Atmospheric Turbulence.
Leland, Robert Patton
In this dissertation, stochastic models for laser propagation in atmospheric turbulence are considered. A review of the existing literature on laser propagation in the atmosphere and white noise theory is presented, with a view toward relating the white noise integral and Ito integral approaches. The laser beam intensity is considered as the solution to a random Schroedinger equation, or forward scattering equation. This model is formulated in a Hilbert space context as an abstract bilinear system with a multiplicative white noise input, as in the literature. The model is also modeled in the Banach space of Fresnel class functions to allow the plane wave case and the application of path integrals. Approximate solutions to the Schroedinger equation of the Trotter-Kato product form are shown to converge for each white noise sample path. The product forms are shown to be physical random variables, allowing an Ito integral representation. The corresponding Ito integrals are shown to converge in mean square, providing a white noise basis for the Stratonovich correction term associated with this equation. Product form solutions for Ornstein -Uhlenbeck process inputs were shown to converge in mean square as the input bandwidth was expanded. A digital simulation of laser propagation in strong turbulence was used to study properties of the beam. Empirical distributions for the irradiance function were estimated from simulated data, and the log-normal and Rice-Nakagami distributions predicted by the classical perturbation methods were seen to be inadequate. A gamma distribution fit the simulated irradiance distribution well in the vicinity of the boresight. Statistics of the beam were seen to converge rapidly as the bandwidth of an Ornstein-Uhlenbeck process was expanded to its white noise limit. Individual trajectories of the beam were presented to illustrate the distortion and bending of the beam due to turbulence. Feynman path integrals were used to calculate an
Directory of Open Access Journals (Sweden)
Yanchuan Mou
2017-10-01
Full Text Available Given the rapidly developing processes in the housing market of China, the significant regional difference in housing prices has become a serious issue that requires a further understanding of the underlying mechanisms. Most of the extant regression models are standard global modeling techniques that do not take spatial non-stationarity into consideration, thereby making them unable to reflect the spatial nature of the data and introducing significant bias into the prediction results. In this study, the geographically weighted regression model (GWR was applied to examine the local association between housing price and its potential determinants, which were selected in view of the housing supply and demand in 338 cities across mainland China. Non-stationary relationships were obtained, and such observation could be summarized as follows: (1 the associations between land price and housing price are all significant and positive yet having different magnitudes; (2 the relationship between supplied amount of residential land and housing price is not statistically significant for 272 of the 338 cities, thereby indicating that the adjustment of supplied land has a slight effect on housing price for most cities; and (3 the significance, direction, and magnitude of the relationships between the other three factors (i.e., urbanization rate, average wage of urban employees, proportion of renters and housing price vary across the 338 cities. Based on these findings, this paper discusses some key issues relating to the spatial variations, combined with local economic conditions and suggests housing regulation policies that could facilitate the sustainable development of the Chinese housing market.
Enhancement and Noise Statistics Estimation for Non-Stationary Voiced Speech
DEFF Research Database (Denmark)
Nørholm, Sidsel Marie; Jensen, Jesper Rindom; Christensen, Mads Græsbøll
2016-01-01
In this paper, single channel speech enhancement in the time domain is considered. We address the problem of modelling non-stationary speech by describing the voiced speech parts by a harmonic linear chirp model instead of using the traditional harmonic model. This means that the speech signal...... through simulations on synthetic and speech signals, that the chirp versions of the filters perform better than their harmonic counterparts in terms of output signal-to-noise ratio (SNR) and signal reduction factor. For synthetic signals, the output SNR for the harmonic chirp APES based filter...... is increased 3 dB compared to the harmonic APES based filter at an input SNR of 10 dB, and at the same time the signal reduction factor is decreased. For speech signals, the increase is 1.5 dB along with a decrease in the signal reduction factor of 0.7. As an implicit part of the APES filter, a noise...
Calculation of nonstationary two-dimensional temperature field in a tube wall in burnout
International Nuclear Information System (INIS)
Kashcheev, V.M.; Pykhtina, T.V.; Yur'ev, Yu.S.
1977-01-01
Numerically solved is a nonstationary two-dimensional equation of heat conduction for a tube wall of fuel element simulator with arbitrary energy release. The tube is heat-insulated from the outside. The vapour-liquid mixture flows inside the tube. The burnout is realized, when the heat transfer coefficient corresponds to the developed boiling in one part of the tube, and to the deteriorated regime in the other part of it. The thermal losses are regarded on both ends of the tube. Given are the statement of the problem, the algorithm of the solution, the results of the test adjusting problem. Obtained is the satisfactory agreement of calculated fixed temperature with experimental one
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-01-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
-run and the short-run dynamic behaviour of the volatilities. The structure of the conditional correlation matrix is assumed to be either time independent or to vary over time. We apply our model to pairs of seven daily stock returns belonging to the S&P 500 composite index and traded at the New York Stock Exchange......In this paper we investigate the effects of careful modelling the long-run dynamics of the volatilities of stock market returns on the conditional correlation structure. To this end we allow the individual unconditional variances in Conditional Correlation GARCH models to change smoothly over time...... by incorporating a nonstationary component in the variance equations. The modelling technique to determine the parametric structure of this time-varying component is based on a sequence of specification Lagrange multiplier-type tests derived in Amado and Teräsvirta (2011). The variance equations combine the long...
Unveiling non-stationary coupling between Amazon and ocean during recent extreme events
Ramos, Antônio M. de T.; Zou, Yong; de Oliveira, Gilvan Sampaio; Kurths, Jürgen; Macau, Elbert E. N.
2018-02-01
The interplay between extreme events in the Amazon's precipitation and the anomaly in the temperature of the surrounding oceans is not fully understood, especially its causal relations. In this paper, we investigate the climatic interaction between these regions from 1999 until 2012 using modern tools of complex system science. We identify the time scale of the coupling quantitatively and unveil the non-stationary influence of the ocean's temperature. The findings show consistently the distinctions between the coupling in the recent major extreme events in Amazonia, such as the two droughts that happened in 2005 and 2010 and the three floods during 1999, 2009 and 2012. Interestingly, the results also reveal the influence over the anomalous precipitation of Southwest Amazon has become increasingly lagged. The analysis can shed light on the underlying dynamics of the climate network system and consequently can improve predictions of extreme rainfall events.
A nonstationary Markov transition model for computing the relative risk of dementia before death
Yu, Lei; Griffith, William S.; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.
2010-01-01
This paper investigates the long-term behavior of the k-step transition probability matrix for a nonstationary discrete time Markov chain in the context of modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. The authors derive formulas for the following absorption statistics: (1) the relative risk of absorption between competing absorbing states, and (2) the mean and variance of the number of visits among the transient states before absorption. Since absorption is not guaranteed, sufficient conditions are discussed to ensure that the substochastic matrix associated with transitions among transient states converges to zero in limit. Results are illustrated with an application to the Nun Study, a cohort of 678 participants, 75 to 107 years of age, followed longitudinally with up to ten cognitive assessments over a fifteen-year period. PMID:20087848
Markov-switching model for nonstationary runoff conditioned on El Nino information
DEFF Research Database (Denmark)
Gelati, Emiliano; Madsen, H.; Rosbjerg, Dan
2010-01-01
We define a Markov-modulated autoregressive model with exogenous input (MARX) to generate runoff scenarios using climatic information. Runoff parameterization is assumed to be conditioned on a hidden climate state following a Markov chain, where state transition probabilities are functions...... of the climatic input. MARX allows stochastic modeling of nonstationary runoff, as runoff anomalies are described by a mixture of autoregressive models with exogenous input, each one corresponding to a climate state. We apply MARX to inflow time series of the Daule Peripa reservoir (Ecuador). El Nino Southern...... Oscillation (ENSO) information is used to condition runoff parameterization. Among the investigated ENSO indexes, the NINO 1+2 sea surface temperature anomalies and the trans-Nino index perform best as predictors. In the perspective of reservoir optimization at various time scales, MARX produces realistic...
Virtual cathode regime in nonstationary electric high-current discharge in hydrogen
International Nuclear Information System (INIS)
Baksht, F.G.; Borodin, V.S.; Zhuravlev, V.N.
1988-01-01
Virtual cathode (VC) regime in a non-stationary high-current hydrogen arch is constructed. Basic calculational characteristics of the near-the-cathode layer are presented. The calculation was conducted for a 1 cm long cathode under 2x10 4 A/cm 2 current density in pulse and 10 atm. pressure. A rectangular current pulse was considered. It is shown that VC formation is caused by electron temperature reduction in the near-the-cathode area. This results in the reduction of ion flux from plasma to the cathode surface and finally in the change of a sign of space charge and field intensity near the surface. Under the transition to VC regime only the cathode temperature and its effective work function are practically changed, while the rest of parameters remain approximately constant
Robust suppression of nonstationary power-line interference in electrocardiogram signals
International Nuclear Information System (INIS)
Li, Guojun; Zeng, Xiaopin; Zhou, Yu; Liu, Guojin; Zhou, Xichuan; Zhou, Xiaona
2012-01-01
It is a challenge to suppress time-varying power-line interference (PLI) with various levels in electrocardiogram (ECG) signals. Most previous attempts of tracking and suppressing the nonstationary PLI signal are based on the least-squares (LS) algorithm. This makes these methods susceptible to QRS complex in suppressing a low-level PLI signal which is frequently coupled in battery-operated ECG equipment. To address the limitation of LS-based methods, this study presents a robust PLI suppression system based on a robust extension of the Kalman filter. In addition, we used an improved version of empirical mode decomposition to further attenuate the QRS complex. Experiments show that our system could effectively suppress the PLI while preserving meaningful ECG components at various interference levels. (paper)
Stochastic Geometric Models with Non-stationary Spatial Correlations in Lagrangian Fluid Flows
Gay-Balmaz, François; Holm, Darryl D.
2018-06-01
Inspired by spatiotemporal observations from satellites of the trajectories of objects drifting near the surface of the ocean in the National Oceanic and Atmospheric Administration's "Global Drifter Program", this paper develops data-driven stochastic models of geophysical fluid dynamics (GFD) with non-stationary spatial correlations representing the dynamical behaviour of oceanic currents. Three models are considered. Model 1 from Holm (Proc R Soc A 471:20140963, 2015) is reviewed, in which the spatial correlations are time independent. Two new models, called Model 2 and Model 3, introduce two different symmetry breaking mechanisms by which the spatial correlations may be advected by the flow. These models are derived using reduction by symmetry of stochastic variational principles, leading to stochastic Hamiltonian systems, whose momentum maps, conservation laws and Lie-Poisson bracket structures are used in developing the new stochastic Hamiltonian models of GFD.
Nonstationary modeling of a long record of rainfall and temperature over Rome
Villarini, Gabriele; Smith, James A.; Napolitano, Francesco
2010-10-01
A long record (1862-2004) of seasonal rainfall and temperature from the Rome observatory of Collegio Romano are modeled in a nonstationary framework by means of the Generalized Additive Models in Location, Scale and Shape (GAMLSS). Modeling analyses are used to characterize nonstationarities in rainfall and related climate variables. It is shown that the GAMLSS models are able to represent the magnitude and spread in the seasonal time series with parameters which are a smooth function of time. Covariate analyses highlight the role of seasonal and interannual variability of large-scale climate forcing, as reflected in three teleconnection indexes (Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Mediterranean Index), for modeling seasonal rainfall and temperature over Rome. In particular, the North Atlantic Oscillation is a significant predictor during the winter, while the Mediterranean Index is a significant predictor for almost all seasons.
Mathematical modeling of non-stationary gas flow in gas pipeline
Fetisov, V. G.; Nikolaev, A. K.; Lykov, Y. V.; Duchnevich, L. N.
2018-03-01
An analysis of the operation of the gas transportation system shows that for a considerable part of time pipelines operate in an unsettled regime of gas movement. Its pressure and flow rate vary along the length of pipeline and over time as a result of uneven consumption and selection, switching on and off compressor units, shutting off stop valves, emergence of emergency leaks. The operational management of such regimes is associated with difficulty of reconciling the operating modes of individual sections of gas pipeline with each other, as well as with compressor stations. Determining the grounds that cause change in the operating mode of the pipeline system and revealing patterns of these changes determine the choice of its parameters. Therefore, knowledge of the laws of changing the main technological parameters of gas pumping through pipelines in conditions of non-stationary motion is of great importance for practice.
Medina, Daniel C; Findley, Sally E; Guindo, Boubacar; Doumbia, Seydou
2007-11-21
Much of the developing world, particularly sub-Saharan Africa, exhibits high levels of morbidity and mortality associated with diarrhea, acute respiratory infection, and malaria. With the increasing awareness that the aforementioned infectious diseases impose an enormous burden on developing countries, public health programs therein could benefit from parsimonious general-purpose forecasting methods to enhance infectious disease intervention. Unfortunately, these disease time-series often i) suffer from non-stationarity; ii) exhibit large inter-annual plus seasonal fluctuations; and, iii) require disease-specific tailoring of forecasting methods. In this longitudinal retrospective (01/1996-06/2004) investigation, diarrhea, acute respiratory infection of the lower tract, and malaria consultation time-series are fitted with a general-purpose econometric method, namely the multiplicative Holt-Winters, to produce contemporaneous on-line forecasts for the district of Niono, Mali. This method accommodates seasonal, as well as inter-annual, fluctuations and produces reasonably accurate median 2- and 3-month horizon forecasts for these non-stationary time-series, i.e., 92% of the 24 time-series forecasts generated (2 forecast horizons, 3 diseases, and 4 age categories = 24 time-series forecasts) have mean absolute percentage errors circa 25%. The multiplicative Holt-Winters forecasting method: i) performs well across diseases with dramatically distinct transmission modes and hence it is a strong general-purpose forecasting method candidate for non-stationary epidemiological time-series; ii) obliquely captures prior non-linear interactions between climate and the aforementioned disease dynamics thus, obviating the need for more complex disease-specific climate-based parametric forecasting methods in the district of Niono; furthermore, iii) readily decomposes time-series into seasonal components thereby potentially assisting with programming of public health interventions
Luke, Adam; Vrugt, Jasper A.; AghaKouchak, Amir; Matthew, Richard; Sanders, Brett F.
2017-07-01
Nonstationary extreme value analysis (NEVA) can improve the statistical representation of observed flood peak distributions compared to stationary (ST) analysis, but management of flood risk relies on predictions of out-of-sample distributions for which NEVA has not been comprehensively evaluated. In this study, we apply split-sample testing to 1250 annual maximum discharge records in the United States and compare the predictive capabilities of NEVA relative to ST extreme value analysis using a log-Pearson Type III (LPIII) distribution. The parameters of the LPIII distribution in the ST and nonstationary (NS) models are estimated from the first half of each record using Bayesian inference. The second half of each record is reserved to evaluate the predictions under the ST and NS models. The NS model is applied for prediction by (1) extrapolating the trend of the NS model parameters throughout the evaluation period and (2) using the NS model parameter values at the end of the fitting period to predict with an updated ST model (uST). Our analysis shows that the ST predictions are preferred, overall. NS model parameter extrapolation is rarely preferred. However, if fitting period discharges are influenced by physical changes in the watershed, for example from anthropogenic activity, the uST model is strongly preferred relative to ST and NS predictions. The uST model is therefore recommended for evaluation of current flood risk in watersheds that have undergone physical changes. Supporting information includes a MATLAB® program that estimates the (ST/NS/uST) LPIII parameters from annual peak discharge data through Bayesian inference.
Cannon, A. J.
2009-12-01
Parameters in a Generalized Extreme Value (GEV) distribution are specified as a function of covariates using a conditional density network (CDN), which is a probabilistic extension of the multilayer perceptron neural network. If the covariate is time, or is dependent on time, then the GEV-CDN model can be used to perform nonlinear, nonstationary GEV analysis of hydrological or climatological time series. Due to the flexibility of the neural network architecture, the model is capable of representing a wide range of nonstationary relationships. Model parameters are estimated by generalized maximum likelihood, an approach that is tailored to the estimation of GEV parameters from geophysical time series. Model complexity is identified using the Bayesian information criterion and the Akaike information criterion with small sample size correction. Monte Carlo simulations are used to validate GEV-CDN performance on four simple synthetic problems. The model is then demonstrated on precipitation data from southern California, a series that exhibits nonstationarity due to interannual/interdecadal climatic variability. A hierarchy of models can be defined by adjusting three aspects of the GEV-CDN model architecture: (i) by specifying either a linear or a nonlinear hidden-layer activation function; (ii) by adjusting the number of hidden-layer nodes; or (iii) by disconnecting weights leading to output-layer nodes. To illustrate, five GEV-CDN models are shown here in order of increasing complexity for the case of a single covariate, which, in this case, is assumed to be time. The shape parameter is assumed to be constant in all models, although this is not a requirement of the GEV-CDN framework.
Real-time reservoir operation considering non-stationary inflow prediction
Zhao, J.; Xu, W.; Cai, X.; Wang, Z.
2011-12-01
Stationarity of inflow has been a basic assumption for reservoir operation rule design, which is now facing challenges due to climate change and human interferences. This paper proposes a modeling framework to incorporate non-stationary inflow prediction for optimizing the hedging operation rule of large reservoirs with multiple-year flow regulation capacity. A multi-stage optimization model is formulated and a solution algorithm based on the optimality conditions is developed to incorporate non-stationary annual inflow prediction through a rolling, dynamic framework that updates the prediction from period to period and adopt the updated prediction in reservoir operation decision. The prediction model is ARIMA(4,1,0), in which parameter 4 stands for the order of autoregressive, 1 represents a linear trend, and 0 is the order of moving average. The modeling framework and solution algorithm is applied to the Miyun reservoir in China, determining a yearly operating schedule during the period from 1996 to 2009, during which there was a significant declining trend of reservoir inflow. Different operation policy scenarios are modeled, including standard operation policy (SOP, matching the current demand as much as possible), hedging rule (i.e., leaving a certain amount of water for future to avoid large risk of water deficit) with forecast from ARIMA (HR-1), hedging (HR) with perfect forecast (HR-2 ). Compared to the results of these scenarios to that of the actual reservoir operation (AO), the utility of the reservoir operation under HR-1 is 3.0% lower than HR-2, but 3.7% higher than the AO and 14.4% higher than SOP. Note that the utility under AO is 10.3% higher than that under SOP, which shows that a certain level of hedging under some inflow prediction or forecast was used in the real-world operation. Moreover, the impacts of discount rate and forecast uncertainty level on the operation will be discussed.
Real-Time Emulation of Nonstationary Channels in Safety-Relevant Vehicular Scenarios
Directory of Open Access Journals (Sweden)
Golsa Ghiaasi
2018-01-01
Full Text Available This paper proposes and discusses the architecture for a real-time vehicular channel emulator capable of reproducing the input/output behavior of nonstationary time-variant radio propagation channels in safety-relevant vehicular scenarios. The vehicular channel emulator architecture aims at a hardware implementation which requires minimal hardware complexity for emulating channels with the varying delay-Doppler characteristics of safety-relevant vehicular scenarios. The varying delay-Doppler characteristics require real-time updates to the multipath propagation model for each local stationarity region. The vehicular channel emulator is used for benchmarking the packet error performance of commercial off-the-shelf (COTS vehicular IEEE 802.11p modems and a fully software-defined radio-based IEEE 802.11p modem stack. The packet error ratio (PER estimated from temporal averaging over a single virtual drive and the packet error probability (PEP estimated from ensemble averaging over repeated virtual drives are evaluated and compared for the same vehicular scenario. The proposed architecture is realized as a virtual instrument on National Instruments™ LabVIEW. The National Instrument universal software radio peripheral with reconfigurable input-output (USRP-Rio 2953R is used as the software-defined radio platform for implementation; however, the results and considerations reported are of general purpose and can be applied to other platforms. Finally, we discuss the PER performance of the modem for two categories of vehicular channel models: a vehicular nonstationary channel model derived for urban single lane street crossing scenario of the DRIVEWAY’09 measurement campaign and the stationary ETSI models.
International Nuclear Information System (INIS)
La Pointe, P.R.
1994-11-01
This report describes the comparison of stationary and non-stationary geostatistical models for the purpose of inferring block-scale hydraulic conductivity values from packer tests at Aespoe. The comparison between models is made through the evaluation of cross-validation statistics for three experimental designs. The first experiment consisted of a 'Delete-1' test previously used at Finnsjoen. The second test consisted of 'Delete-10%' and the third test was a 'Delete-50%' test. Preliminary data analysis showed that the 3 m and 30 m packer test data can be treated as a sample from a single population for the purposes of geostatistical analyses. Analysis of the 3 m data does not indicate that there are any systematic statistical changes with depth, rock type, fracture zone vs non-fracture zone or other mappable factor. Directional variograms are ambiguous to interpret due to the clustered nature of the data, but do not show any obvious anisotropy that should be accounted for in geostatistical analysis. Stationary analysis suggested that there exists a sizeable spatially uncorrelated component ('Nugget Effect') in the 3 m data, on the order of 60% of the observed variance for the various models fitted. Four different nested models were automatically fit to the data. Results for all models in terms of cross-validation statistics were very similar for the first set of validation tests. Non-stationary analysis established that both the order of drift and the order of the intrinsic random functions is low. This study also suggests that conventional cross-validation studies and automatic variogram fitting are not necessarily evaluating how well a model will infer block scale hydraulic conductivity values. 20 refs, 20 figs, 14 tabs
Flood frequency analysis for nonstationary annual peak records in an urban drainage basin
Villarini, G.; Smith, J.A.; Serinaldi, F.; Bales, J.; Bates, P.D.; Krajewski, W.F.
2009-01-01
Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110 km2) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1 m3 s- 1 km- 2 to a maximum of 5.1 m3 s- 1 km- 2. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2 m3 s- 1 km- 2). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2 m3 s- 1 km- 2 ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades. ?? 2009 Elsevier Ltd.
Flood frequency analysis for nonstationary annual peak records in an urban drainage basin
Villarini, Gabriele; Smith, James A.; Serinaldi, Francesco; Bales, Jerad; Bates, Paul D.; Krajewski, Witold F.
2009-08-01
Flood frequency analysis in urban watersheds is complicated by nonstationarities of annual peak records associated with land use change and evolving urban stormwater infrastructure. In this study, a framework for flood frequency analysis is developed based on the Generalized Additive Models for Location, Scale and Shape parameters (GAMLSS), a tool for modeling time series under nonstationary conditions. GAMLSS is applied to annual maximum peak discharge records for Little Sugar Creek, a highly urbanized watershed which drains the urban core of Charlotte, North Carolina. It is shown that GAMLSS is able to describe the variability in the mean and variance of the annual maximum peak discharge by modeling the parameters of the selected parametric distribution as a smooth function of time via cubic splines. Flood frequency analyses for Little Sugar Creek (at a drainage area of 110km) show that the maximum flow with a 0.01-annual probability (corresponding to 100-year flood peak under stationary conditions) over the 83-year record has ranged from a minimum unit discharge of 2.1mskm to a maximum of 5.1mskm. An alternative characterization can be made by examining the estimated return interval of the peak discharge that would have an annual exceedance probability of 0.01 under the assumption of stationarity (3.2mskm). Under nonstationary conditions, alternative definitions of return period should be adapted. Under the GAMLSS model, the return interval of an annual peak discharge of 3.2mskm ranges from a maximum value of more than 5000 years in 1957 to a minimum value of almost 8 years for the present time (2007). The GAMLSS framework is also used to examine the links between population trends and flood frequency, as well as trends in annual maximum rainfall. These analyses are used to examine evolving flood frequency over future decades.
Modelling non-stationary annual maximum flood heights in the lower Limpopo River basin of Mozambique
Directory of Open Access Journals (Sweden)
Daniel Maposa
2016-05-01
Full Text Available In this article we fit a time-dependent generalised extreme value (GEV distribution to annual maximum flood heights at three sites: Chokwe, Sicacate and Combomune in the lower Limpopo River basin of Mozambique. A GEV distribution is fitted to six annual maximum time series models at each site, namely: annual daily maximum (AM1, annual 2-day maximum (AM2, annual 5-day maximum (AM5, annual 7-day maximum (AM7, annual 10-day maximum (AM10 and annual 30-day maximum (AM30. Non-stationary time-dependent GEV models with a linear trend in location and scale parameters are considered in this study. The results show lack of sufficient evidence to indicate a linear trend in the location parameter at all three sites. On the other hand, the findings in this study reveal strong evidence of the existence of a linear trend in the scale parameter at Combomune and Sicacate, whilst the scale parameter had no significant linear trend at Chokwe. Further investigation in this study also reveals that the location parameter at Sicacate can be modelled by a nonlinear quadratic trend; however, the complexity of the overall model is not worthwhile in fit over a time-homogeneous model. This study shows the importance of extending the time-homogeneous GEV model to incorporate climate change factors such as trend in the lower Limpopo River basin, particularly in this era of global warming and a changing climate. Keywords: nonstationary extremes; annual maxima; lower Limpopo River; generalised extreme value
International Nuclear Information System (INIS)
Davis, A.; Wiscombe, W.; Cahalan, R.; Marshak, A.
1994-01-01
Geophysical data rarely show any smoothness at any scale, and this often makes comparison with theoretical model output difficult. However, highly fluctuating signals and fractual structures are typical of open dissipative systems with nonlinear dynamics, the focus of most geophysical research. High levels of variability are excited over a large range of scales by the combined actions of external forcing and internal instability. At very small scales we expect geophysical fields to be smooth, but these are rarely resolved with available instrumentation or simulation tools; nondifferentiable and even discontinuous models are therefore in order. We need methods of statistically analyzing geophysical data, whether measured in situ, remotely sensed or even generated by a computer model, that are adapted to these characteristics. An important preliminary task is to define statistically stationary features in generally nonstationary signals. We first discuss a simple criterion for stationarity in finite data streams that exhibit power law energy spectra and then, guided by developments in turbulence studies, we advocate the use of two ways of analyzing the scale dependence of statistical information: singular measures and qth order structure functions. In nonstationary situations, the approach based on singular measures seeks power law behavior in integrals over all possible scales of a nonnegative stationary field derived from the data, leading to a characterization of the intermittency in this field. In contrast, the approach based on structure functions uses the signal itself, seeking power laws for the statistical moments of absolute increments over arbitrarily large scales, leading to a characterization of the prevailing nonstationarity in both quantitative and qualitative terms. We explain graphically, step by step, both multifractal statistics which are largely complementary to each other. 45 refs., 13 figs., 2 tabs
Early stages of wind wave and drift current generation under non-stationary wind conditions.
Robles-Diaz, Lucia; Ocampo-Torres, Francisco J.; Branger, Hubert
2016-04-01
Generation and amplification mechanisms of ocean waves are well understood under constant wind speed or limited fetch conditions. Under these situations, the momentum and energy transfers from air to water are also quite well known. However during the wind field evolution over the ocean, we may observe sometime high wind acceleration/deceleration situations (e.g. Mexican Tehuano or Mediterranean Mistral wind systems). The evolution of wave systems under these conditions is not well understood. The purpose of these laboratory experiments is to better understand the early stages of water-waves and surface-drift currents under non-stationary wind conditions and to determine the balance between transfers creating waves and surface currents during non-equilibrium situations. The experiments were conducted in the Institut Pythéas wind-wave facility in Marseille-France. The wave tank is 40 m long, 2.7 m wide and 1 m deep. The air section is 50 m long, 3 m wide and 1.8 m height. We used 11 different resistive wave-gauges located along the tank. The momentum fluxes in the air column were estimated from single and X hot-film anemometer measurements. The sampling frequency for wind velocity and surface displacement measurements was 256 Hz. Water-current measurements were performed with a profiling velocimeter. This device measures the first 3.5 cm of the water column with a frequency rate of 100Hz. During the experiments, the wind intensity was abruptly modified with a constant acceleration and deceleration over time. We observed that wind drag coefficient values for accelerated wind periods are lower than the ones reported in previous studies for constant wind speed (Large and Pond 1981; Ocampo-Torres et al. 2010; Smith 1980; Yelland and Taylor 1996). This is probably because the turbulent boundary layer is not completely developed during the increasing-wind sequence. As it was reported in some theoretical studies (Miles 1957; Phillips 1957; Kahma and Donelan 1988), we
International Nuclear Information System (INIS)
Liu, Yangqing; Tan, Yi; Xie, Huiqiao; Wang, Wenhao; Gao, Zhe
2014-01-01
An improved Hilbert-Huang transform method is developed to the time-frequency analysis of non-stationary signals in tokamak plasmas. Maximal overlap discrete wavelet packet transform rather than wavelet packet transform is proposed as a preprocessor to decompose a signal into various narrow-band components. Then, a correlation coefficient based selection method is utilized to eliminate the irrelevant intrinsic mode functions obtained from empirical mode decomposition of those narrow-band components. Subsequently, a time varying vector autoregressive moving average model instead of Hilbert spectral analysis is performed to compute the Hilbert spectrum, i.e., a three-dimensional time-frequency distribution of the signal. The feasibility and effectiveness of the improved Hilbert-Huang transform method is demonstrated by analyzing a non-stationary simulated signal and actual experimental signals in fusion plasmas
Energy Technology Data Exchange (ETDEWEB)
Zentner, I. [IMSIA, UMR EDF-ENSTA-CNRS-CEA 9219, Université Paris-Saclay, 828 Boulevard des Maréchaux, 91762 Palaiseau Cedex (France); Ferré, G., E-mail: gregoire.ferre@ponts.org [CERMICS – Ecole des Ponts ParisTech, 6 et 8 avenue Blaise Pascal, Cité Descartes, Champs sur Marne, 77455 Marne la Vallée Cedex 2 (France); Poirion, F. [Department of Structural Dynamics and Aeroelasticity, ONERA, BP 72, 29 avenue de la Division Leclerc, 92322 Chatillon Cedex (France); Benoit, M. [Institut de Recherche sur les Phénomènes Hors Equilibre (IRPHE), UMR 7342 (CNRS, Aix-Marseille Université, Ecole Centrale Marseille), 49 rue Frédéric Joliot-Curie, BP 146, 13384 Marseille Cedex 13 (France)
2016-06-01
In this paper, a new method for the identification and simulation of non-Gaussian and non-stationary stochastic fields given a database is proposed. It is based on two successive biorthogonal decompositions aiming at representing spatio–temporal stochastic fields. The proposed double expansion allows to build the model even in the case of large-size problems by separating the time, space and random parts of the field. A Gaussian kernel estimator is used to simulate the high dimensional set of random variables appearing in the decomposition. The capability of the method to reproduce the non-stationary and non-Gaussian features of random phenomena is illustrated by applications to earthquakes (seismic ground motion) and sea states (wave heights).
Feng, Ke; Wang, Kesheng; Ni, Qing; Zuo, Ming J.; Wei, Dongdong
2017-11-01
Planetary gearbox is a critical component for rotating machinery. It is widely used in wind turbines, aerospace and transmission systems in heavy industry. Thus, it is important to monitor planetary gearboxes, especially for fault diagnostics, during its operational conditions. However, in practice, operational conditions of planetary gearbox are often characterized by variations of rotational speeds and loads, which may bring difficulties for fault diagnosis through the measured vibrations. In this paper, phase angle data extracted from measured planetary gearbox vibrations is used for fault detection under non-stationary operational conditions. Together with sample entropy, fault diagnosis on planetary gearbox is implemented. The proposed scheme is explained and demonstrated in both simulation and experimental studies. The scheme proves to be effective and features advantages on fault diagnosis of planetary gearboxes under non-stationary operational conditions.
Directory of Open Access Journals (Sweden)
E.M. Almukhametova
2018-06-01
Full Text Available Abstract. The last few years, work has been carried out to study the effectiveness of non-stationary exposure in the highly viscous oil field Northern Buzachi (Republic of Kazakhstan. It has been proved that this technology is quite effective in the development of highly viscous oil reservoirs, however, in order to constantly maintain high technological effect, a constant modification of this technology is required, since it has a characteristic feature of rapid «aging». Further search for the conditions of effective application of non-stationary exposure on highly-viscous oil deposits can be carried out in two directions: the implementation of non-stationary exposure in new areas with other reservoir parameters and the change in the parameters of non-stationary exposure technology (including combining with other technologies in areas where this technology is already in use. Both approaches are used on the Northern Buzachi field. Thus, the positive experience of using non-stationary waterflooding in combination with changing direction of the filtration flow in the section of the seventh block of the Northern Buzachi field allowed us to recommend new sites for the implementation of this technology. With the participation of the author of this work, a non-stationary waterflooding program was developed and implemented on the site of the sixth block (south of the first operational facility.
Kvitko, A. N.
2018-01-01
An algorithm convenient for numerical implementation is proposed for constructing differentiable control functions that transfer a wide class of nonlinear nonstationary systems of ordinary differential equations from an initial state to a given point of the phase space. Constructive sufficient conditions imposed on the right-hand side of the controlled system are obtained under which this transfer is possible. The control of a robotic manipulator is considered, and its numerical simulation is performed.
Huang, Norden E.; Hu, Kun; Yang, Albert C. C.; Chang, Hsing-Chih; Jia, Deng; Liang, Wei-Kuang; Yeh, Jia Rong; Kao, Chu-Lan; Juan, Chi-Hung; Peng, Chung Kang; Meijer, Johanna H.; Wang, Yung-Hung; Long, Steven R.; Wu, Zhauhua
2016-01-01
The Holo-Hilbert spectral analysis (HHSA) method is introduced to cure the deficiencies of traditional spectral analysis and to give a full informational representation of nonlinear and non-stationary data. It uses a nested empirical mode decomposition and Hilbert–Huang transform (HHT) approach to identify intrinsic amplitude and frequency modulations often present in nonlinear systems. Comparisons are first made with traditional spectrum analysis, which usually achieved its results through c...
Energy Technology Data Exchange (ETDEWEB)
Solodov, V G [Kharkov State Automobile and Highway Technical University, Theoretical Mechanics and Hydraulics Department, Kharkov (Ukraine)
1998-12-31
The article describes numerical models and some results of numerical simulation of self-excited oscillatory flow regimes through exhaust diffusers of large steam turbines, operating as a part of compartment (jointly with last stage). The modelling is based on a model of ideal gas flow and full nonstationary 3D formulation and 2nd time and space order explicit Godunov`s scheme. (author) 11 refs.
Energy Technology Data Exchange (ETDEWEB)
Solodov, V.G. [Kharkov State Automobile and Highway Technical University, Theoretical Mechanics and Hydraulics Department, Kharkov (Ukraine)
1997-12-31
The article describes numerical models and some results of numerical simulation of self-excited oscillatory flow regimes through exhaust diffusers of large steam turbines, operating as a part of compartment (jointly with last stage). The modelling is based on a model of ideal gas flow and full nonstationary 3D formulation and 2nd time and space order explicit Godunov`s scheme. (author) 11 refs.
López, J.; Francés, F.
2013-08-01
Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS). Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation) and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.
Directory of Open Access Journals (Sweden)
J. López
2013-08-01
Full Text Available Recent evidences of the impact of persistent modes of regional climate variability, coupled with the intensification of human activities, have led hydrologists to study flood regime without applying the hypothesis of stationarity. In this study, a framework for flood frequency analysis is developed on the basis of a tool that enables us to address the modelling of non-stationary time series, namely, the "generalized additive models for location, scale and shape" (GAMLSS. Two approaches to non-stationary modelling in GAMLSS were applied to the annual maximum flood records of 20 continental Spanish rivers. The results of the first approach, in which the parameters of the selected distributions were modelled as a function of time only, show the presence of clear non-stationarities in the flood regime. In a second approach, the parameters of the flood distributions are modelled as functions of climate indices (Arctic Oscillation, North Atlantic Oscillation, Mediterranean Oscillation and the Western Mediterranean Oscillation and a reservoir index that is proposed in this paper. The results when incorporating external covariates in the study highlight the important role of interannual variability in low-frequency climate forcings when modelling the flood regime in continental Spanish rivers. Also, with this approach it is possible to properly introduce the impact on the flood regime of intensified reservoir regulation strategies. The inclusion of external covariates permits the use of these models as predictive tools. Finally, the application of non-stationary analysis shows that the differences between the non-stationary quantiles and their stationary equivalents may be important over long periods of time.
Modeling fire spatial non-stationary in Portugal using GWR and GAMLSS
Sá, Ana C. L.; Amaral Turkman, Maria A.; Bistinas, Ioannis; Pereira, José M. C.
2014-05-01
Portuguese wildfires are responsible for large environmental, ecological and socio-economic impacts and, in the last decade, vegetation fires consumed on average 140.000ha/year. Portugal has a unique fires-atlas of burnt scar perimeters covering the 1975-2009 period, which allows the assessment of the fire most affected areas. It's crucial to understand the influence of the main drivers of forest fires and its spatial distribution in order to set new management strategies to reduce its impacts. Thus, this study aims at evaluating the spatial stationarity of the fire-environment relationship using two statistical approaches: Geographically Weighted Regression (GWR) and Generalized Additive Models for Location, Scale and Shape (GAMLSS). Analysis was performed using a regular 2kmx2km cell size grid, a total of 21293 observations overlaying the mainland of Portugal. Fire incidence was determined as the number of times each grid cell burned in the 35 years period. For the GWR analysis the group of environmental variables selected as predictors are: ignition source (population density (PD)); vegetation (proportion of forest and shrubland (FORSHR)); and weather (total precipitation of the coldest quarter (PCQ). Results showed that the fire-environment relationship is non-stationary, thus the coefficient estimates of all the predictors vary spatially, both in magnitude and sign. The most statistically significant predictor is FORSHR, followed by the PCQ. Despite the relationship between fire incidence and PD is non-stationary, only 9% of the observations are statistically significant at a 95% level of confidence. When compared with the Ordinary Least Squares (OLS) global model, 53% of the R2 statistic is above the 26% global estimated value, meaning a better explanation of the fire incidence variance with the local model approach. Using the same environmental variables, fire incidence was also modeled using GAMLSS to characterize nonstationarities in fire incidence. It is
Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI
Energy Technology Data Exchange (ETDEWEB)
Chen, Kho Chia; Kane, Ibrahim Lawal; Rahman, Haliza Abd [Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia); Bahar, Arifah [UTM Centre for Industrial and Applied Mathematics (UTM-CIAM), Universiti Teknologi Malaysia, 81310, Johor Bahru and Department of Mathematical Sciences, Faculty of Science, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia); Ting, Chee-Ming [Center for Biomedical Engineering, Universiti Teknologi Malaysia, 81310, Johor Bahru (Malaysia)
2015-02-03
In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.
Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI
Chen, Kho Chia; Bahar, Arifah; Kane, Ibrahim Lawal; Ting, Chee-Ming; Rahman, Haliza Abd
2015-02-01
In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well.
Estimation of stochastic volatility with long memory for index prices of FTSE Bursa Malaysia KLCI
International Nuclear Information System (INIS)
Chen, Kho Chia; Kane, Ibrahim Lawal; Rahman, Haliza Abd; Bahar, Arifah; Ting, Chee-Ming
2015-01-01
In recent years, modeling in long memory properties or fractionally integrated processes in stochastic volatility has been applied in the financial time series. A time series with structural breaks can generate a strong persistence in the autocorrelation function, which is an observed behaviour of a long memory process. This paper considers the structural break of data in order to determine true long memory time series data. Unlike usual short memory models for log volatility, the fractional Ornstein-Uhlenbeck process is neither a Markovian process nor can it be easily transformed into a Markovian process. This makes the likelihood evaluation and parameter estimation for the long memory stochastic volatility (LMSV) model challenging tasks. The drift and volatility parameters of the fractional Ornstein-Unlenbeck model are estimated separately using the least square estimator (lse) and quadratic generalized variations (qgv) method respectively. Finally, the empirical distribution of unobserved volatility is estimated using the particle filtering with sequential important sampling-resampling (SIR) method. The mean square error (MSE) between the estimated and empirical volatility indicates that the performance of the model towards the index prices of FTSE Bursa Malaysia KLCI is fairly well
Thiombiano, Alida N.; El Adlouni, Salaheddine; St-Hilaire, André; Ouarda, Taha B. M. J.; El-Jabi, Nassir
2017-07-01
In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary peaks-over-threshold model. Indeed, the generalized Pareto distribution (GPD) is fitted to excess time series derived from annual averages of independent precipitation amount events above a fixed threshold, the 99th percentile. Only the scale parameter of the fitted distribution is allowed to vary as a function of a covariate. This variability is modeled using B-spline function. Nonlinear correlation and cross-wavelet analysis allowed identifying two dominant climate indices as covariates in the study area, Arctic Oscillation (AO) and Pacific North American (PNA). The nonstationary frequency analysis showed that there is an east-west behavior of the AO index effects on extreme daily precipitation amounts in the study area. Indeed, the higher quantiles of these events are conditional to the AO positive phase in Atlantic Canada, while those in the more southeastern part of Canada, especially in Southern Quebec and Ontario, are negatively related to AO. The negative phase of PNA also gives the best significant correlation in these regions. Moreover, a regression analysis between AO (PNA) index and conditional quantiles provided slope values for the positive phase of the index on the one hand and the negative phase and on the other hand. This statistic allows computing a slope ratio which permits to sustain the nonlinear relation assumption between climate indices and precipitation and the development of the nonstationary GPD model for Southeastern Canada extremes precipitation modeling.
International Nuclear Information System (INIS)
Chang, C C; Hsiao, T C; Kao, S C; Hsu, H Y
2014-01-01
Arterial blood pressure (ABP) is an important indicator of cardiovascular circulation and presents various intrinsic regulations. It has been found that the intrinsic characteristics of blood vessels can be assessed quantitatively by ABP analysis (called reflection wave analysis (RWA)), but conventional RWA is insufficient for assessment during non-stationary conditions, such as the Valsalva maneuver. Recently, a novel adaptive method called empirical mode decomposition (EMD) was proposed for non-stationary data analysis. This study proposed a RWA algorithm based on EMD (EMD-RWA). A total of 51 subjects participated in this study, including 39 healthy subjects and 12 patients with autonomic nervous system (ANS) dysfunction. The results showed that EMD-RWA provided a reliable estimation of reflection time in baseline and head-up tilt (HUT). Moreover, the estimated reflection time is able to assess the ANS function non-invasively, both in normal, healthy subjects and in the patients with ANS dysfunction. EMD-RWA provides a new approach for reflection time estimation in non-stationary conditions, and also helps with non-invasive ANS assessment. (paper)
Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo
2015-04-01
The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.
A multiscale guide to Brownian motion
International Nuclear Information System (INIS)
Grebenkov, Denis S; Belyaev, Dmitry; Jones, Peter W
2016-01-01
We revise the Lévy construction of Brownian motion as a simple though rigorous approach to operate with various Gaussian processes. A Brownian path is explicitly constructed as a linear combination of wavelet-based ‘geometrical features’ at multiple length scales with random weights. Such a wavelet representation gives a closed formula mapping of the unit interval onto the functional space of Brownian paths. This formula elucidates many classical results about Brownian motion (e.g., non-differentiability of its path), providing an intuitive feeling for non-mathematicians. The illustrative character of the wavelet representation, along with the simple structure of the underlying probability space, is different from the usual presentation of most classical textbooks. Similar concepts are discussed for the Brownian bridge, fractional Brownian motion, the Ornstein-Uhlenbeck process, Gaussian free fields, and fractional Gaussian fields. Wavelet representations and dyadic decompositions form the basis of many highly efficient numerical methods to simulate Gaussian processes and fields, including Brownian motion and other diffusive processes in confining domains. (topical review)
Distribution of return point memory states for systems with stochastic inputs
International Nuclear Information System (INIS)
Amann, A; Brokate, M; Rachinskii, D; Temnov, G
2011-01-01
We consider the long term effect of stochastic inputs on the state of an open loop system which exhibits the so-called return point memory. An example of such a system is the Preisach model; more generally, systems with the Preisach type input-state relationship, such as in spin-interaction models, are considered. We focus on the characterisation of the expected memory configuration after the system has been effected by the input for sufficiently long period of time. In the case where the input is given by a discrete time random walk process, or the Wiener process, simple closed form expressions for the probability density of the vector of the main input extrema recorded by the memory state, and scaling laws for the dimension of this vector, are derived. If the input is given by a general continuous Markov process, we show that the distribution of previous memory elements can be obtained from a Markov chain scheme which is derived from the solution of an associated one-dimensional escape type problem. Formulas for transition probabilities defining this Markov chain scheme are presented. Moreover, explicit formulas for the conditional probability densities of previous main extrema are obtained for the Ornstein-Uhlenbeck input process. The analytical results are confirmed by numerical experiments.
Directory of Open Access Journals (Sweden)
Yoo-Geun Ham
2016-01-01
Full Text Available This study introduces a modified version of the incremental analysis updates (IAU, called the nonstationary IAU (NIAU method, to improve the assimilation accuracy of the IAU while keeping the continuity of the analysis. Similar to the IAU, the NIAU is designed to add analysis increments at every model time step to improve the continuity in the intermittent data assimilation. However, unlike the IAU, the NIAU procedure uses time-evolved forcing using the forward operator as corrections to the model. The solution of the NIAU is superior to that of the forward IAU, of which analysis is performed at the beginning of the time window for adding the IAU forcing, in terms of the accuracy of the analysis field. It is because, in the linear systems, the NIAU solution equals that in an intermittent data assimilation method at the end of the assimilation interval. To have the filtering property in the NIAU, a forward operator to propagate the increment is reconstructed with only dominant singular vectors. An illustration of those advantages of the NIAU is given using the simple 40-variable Lorenz model.
Blind Separation of Nonstationary Sources Based on Spatial Time-Frequency Distributions
Directory of Open Access Journals (Sweden)
Zhang Yimin
2006-01-01
Full Text Available Blind source separation (BSS based on spatial time-frequency distributions (STFDs provides improved performance over blind source separation methods based on second-order statistics, when dealing with signals that are localized in the time-frequency (t-f domain. In this paper, we propose the use of STFD matrices for both whitening and recovery of the mixing matrix, which are two stages commonly required in many BSS methods, to provide robust BSS performance to noise. In addition, a simple method is proposed to select the auto- and cross-term regions of time-frequency distribution (TFD. To further improve the BSS performance, t-f grouping techniques are introduced to reduce the number of signals under consideration, and to allow the receiver array to separate more sources than the number of array sensors, provided that the sources have disjoint t-f signatures. With the use of one or more techniques proposed in this paper, improved performance of blind separation of nonstationary signals can be achieved.
Non-stationary hydrologic frequency analysis using B-spline quantile regression
Nasri, B.; Bouezmarni, T.; St-Hilaire, A.; Ouarda, T. B. M. J.
2017-11-01
Hydrologic frequency analysis is commonly used by engineers and hydrologists to provide the basic information on planning, design and management of hydraulic and water resources systems under the assumption of stationarity. However, with increasing evidence of climate change, it is possible that the assumption of stationarity, which is prerequisite for traditional frequency analysis and hence, the results of conventional analysis would become questionable. In this study, we consider a framework for frequency analysis of extremes based on B-Spline quantile regression which allows to model data in the presence of non-stationarity and/or dependence on covariates with linear and non-linear dependence. A Markov Chain Monte Carlo (MCMC) algorithm was used to estimate quantiles and their posterior distributions. A coefficient of determination and Bayesian information criterion (BIC) for quantile regression are used in order to select the best model, i.e. for each quantile, we choose the degree and number of knots of the adequate B-spline quantile regression model. The method is applied to annual maximum and minimum streamflow records in Ontario, Canada. Climate indices are considered to describe the non-stationarity in the variable of interest and to estimate the quantiles in this case. The results show large differences between the non-stationary quantiles and their stationary equivalents for an annual maximum and minimum discharge with high annual non-exceedance probabilities.
Some strange numerical solutions of the non-stationary Navier-Stokes equations in pipes
Energy Technology Data Exchange (ETDEWEB)
Rummler, B.
2001-07-01
A general class of boundary-pressure-driven flows of incompressible Newtonian fluids in three-dimensional pipes with known steady laminar realizations is investigated. Considering the laminar velocity as a 3D-vector-function of the cross-section-circle arguments, we fix the scale for the velocity by the L{sub 2}-norm of the laminar velocity. The usual new variables are introduced to get dimension-free Navier-Stokes equations. The characteristic physical and geometrical quantities are subsumed in the energetic Reynolds number Re and a parameter {psi}, which involves the energetic ratio and the directions of the boundary-driven part and the pressure-driven part of the laminar flow. The solution of non-stationary dimension-free Navier-Stokes equations is sought in the form u=u{sub L}+u, where u{sub L} is the scaled laminar velocity and periodical conditions in center-line-direction are prescribed for u. An autonomous system (S) of ordinary differential equations for the time-dependent coefficients of the spatial Stokes eigenfunction is got by application of the Galerkin-method to the dimension-free Navier-Stokes equations for u. The finite-dimensional approximations u{sub N({lambda}}{sub )} of u are defined in the usual way. (orig.)
Morphology of silver deposits produced by non-stationary steady regimes
International Nuclear Information System (INIS)
Popovski, Orce
2002-01-01
Morphology of silver electro deposits produced by periodical reversing of d.c. pulses was studied. Employing usual electrorefining conditions it is not possible to deposit compact silver layers from Ag non-complexing salts. This is due, mainly, to the high value of silver exchange current density and to the silver crystallographic peculiarity. In order to counteract this phenomenon, instead of usual, (stationer) potential-current regimes, non-stationary one was applied in this study. The effect of phosphate ions in the electrolyte was further clarified. A set of experimental conditions was applied so that silver was electrodeposited under mixed electrochemical and diffusion control. The primar cathodic pulse causes silver to nucleate with high density and nuclei to start to grow. The subsequent anodic pulse (current reversal) lowers the gradient of silver ion concentration and dissolves the most active growth centers as well. The combination of cathodic and anodic pulses diminishes the dendritic growth and helps smoothing of deposit surface to occur. Fine-grained and more compact deposits are produced, as compared to the ones grown in purely potentiostatic conditions. It was found that the addition of phosphate ions as well as the application of intensive electrolyte stirring change the Ag- grain morphology in favor of poli crystal whisker structure. (Author)
Energy Technology Data Exchange (ETDEWEB)
Vehauc, A; Spasojevic, D [Institute of nuclear sciences Boris Kidric, Vinca, Beograd (Yugoslavia)
1970-03-15
Nonstationary temperature field in the fuel element was examined for spatial and time distribution of the specific power generated in the fuel element. Analytical method was developed for calculating the temperature variation in the fuel element of a nuclear reactor for a typical shape of the heat generation function. The method is based on series expansion of the temperature field by self functions and application of Laplace transformation in time coordinate. For numerical calculation of the temperature distribution a computer code was developed based on the proposed method and applied on the ZUSE-Z-23 computer. Razmatrano je nestacionarno temperatursko polje u preseku sipke gorivnog elementa za slucaj prostorne i vremenske raspodele specificne generacije snage u gorivnom elementu. Razradjen je analii postupak odredjivanja promene temperature u gorivu nuklearnog reaktora za tipican oblik funkcije generacije toplote. Postupak se zasniva na razvoju temperaturskog polja po sopstvenim funkcijama i primeni Laplasove transformacije po vremenskoj koordinati. Za efektivno nalazenje temperaturskog polja, postupak je programiran za digitalnu racunsku masinu ZUSE-Z-23 (author)
Marchese, N; Cannuli, A; Caccamo, M T; Pace, C
2017-01-01
Neutron sources are increasingly employed in a wide range of research fields. For some specific purposes an alternative to existing large-scale neutron scattering facilities, can be offered by the new generation of portable neutron devices. This review reports an overview for such recently available neutron generators mainly addressed to biophysics applications with specific reference to portable non-stationary neutron generators applied in Neutron Activation Analysis (NAA). The review reports a description of a typical portable neutron generator set-up addressed to biophysics applications. New generation portable neutron devices, for some specific applications, can constitute an alternative to existing large-scale neutron scattering facilities. Deuterium-Deuterium pulsed neutron sources able to generate 2.5MeV neutrons, with a neutron yield of 1.0×10 6 n/s, a pulse rate of 250Hz to 20kHz and a duty factor varying from 5% to 100%, when combined with solid-state photon detectors, show that this kind of compact devices allow rapid and user-friendly elemental analysis. "This article is part of a Special Issue entitled "Science for Life" Guest Editor: Dr. Austen Angell, Dr. Salvatore Magazù and Dr. Federica Migliardo". Copyright © 2016 Elsevier B.V. All rights reserved.
Cicone, A.; Zhou, H.; Piersanti, M.; Materassi, M.; Spogli, L.
2017-12-01
Nonlinear and nonstationary signals are ubiquitous in real life. Their decomposition and analysis is of crucial importance in many research fields. Traditional techniques, like Fourier and wavelet Transform have been proved to be limited in this context. In the last two decades new kind of nonlinear methods have been developed which are able to unravel hidden features of these kinds of signals. In this poster we present a new method, called Adaptive Local Iterative Filtering (ALIF). This technique, originally developed to study mono-dimensional signals, unlike any other algorithm proposed so far, can be easily generalized to study two or higher dimensional signals. Furthermore, unlike most of the similar methods, it does not require any a priori assumption on the signal itself, so that the technique can be applied as it is to any kind of signals. Applications of ALIF algorithm to real life signals analysis will be presented. Like, for instance, the behavior of the water level near the coastline in presence of a Tsunami, length of the day signal, pressure measured at ground level on a global grid, radio power scintillation from GNSS signals,
Kinetic features and non-stationary electron trapping in paraxial magnetic nozzles
Sánchez-Arriaga, G.; Zhou, J.; Ahedo, E.; Martínez-Sánchez, M.; Ramos, J. J.
2018-03-01
The paraxial expansion of a collisionless plasma jet into vacuum, guided by a magnetic nozzle, is studied with an Eulerian and non-stationary Vlasov-Poisson solver. Parametric analyzes varying the magnetic field expansion rate, the size of the simulation box, and the electrostatic potential fall are presented. After choosing the potential fall leading to a zero net current beam, the steady states of the simulations exhibit a quasi-neutral region followed by a downstream sheath. The latter, an unavoidable consequence of the finite size of the computational domain, does not affect the quasi-neutral region if the box size is chosen appropriately. The steady state presents a strong decay of the perpendicular temperature of the electrons, whose profile versus the inverse of the magnetic field does not depend on the expansion rate within the quasi-neutral region. As a consequence, the electron distribution function is highly anisotropic downstream. The simulations revealed that the ions reach a higher velocity during the transient than in the steady state and their distribution functions are not far from mono-energetic. The density percentage of the population of electrons trapped during the transient, which is computed self-consistently by the code, is up to 25% of the total electron density in the quasi-neutral region. It is demonstrated that the exact amount depends on the history of the system and the steady state is not unique. Nevertheless, the amount of trapped electrons is smaller than the one assumed heuristically by kinetic stationary theories.
A unique Fock quantization for fields in non-stationary spacetimes
International Nuclear Information System (INIS)
Cortez, Jerónimo; Marugán, Guillermo A. Mena; Olmedo, Javier; Velhinho, José M.
2010-01-01
In curved spacetimes, the lack of criteria for the construction of a unique quantization is a fundamental problem undermining the significance of the predictions of quantum field theory. Inequivalent quantizations lead to different physics. Recently, however, some uniqueness results have been obtained for fields in non-stationary settings. In particular, for vacua that are invariant under the background symmetries, a unitary implementation of the classical evolution suffices to pick up a unique Fock quantization in the case of Klein-Gordon fields with time-dependent mass, propagating in a static spacetime whose spatial sections are three-spheres. In fact, the field equation can be reinterpreted as describing the propagation in a Friedmann-Robertson-Walker spacetime after a suitable scaling of the field by a function of time. For this class of fields, we prove here an even stronger result about the Fock quantization: the uniqueness persists when one allows for linear time-dependent transformations of the field in order to account for a scaling by background functions. In total, paying attention to the dynamics, there exists a preferred choice of quantum field, and only one SO(4)-invariant Fock representation for it that respects the standard probabilistic interpretation along the evolution. The result has relevant implications e.g. in cosmology
A Review of ENSO Influence on the North Atlantic. A Non-Stationary Signal
Directory of Open Access Journals (Sweden)
Belén Rodríguez-Fonseca
2016-06-01
Full Text Available The atmospheric seasonal cycle of the North Atlantic region is dominated by meridional movements of the circulation systems: from the tropics, where the West African Monsoon and extreme tropical weather events take place, to the extratropics, where the circulation is dominated by seasonal changes in the jetstream and extratropical cyclones. Climate variability over the North Atlantic is controlled by various mechanisms. Atmospheric internal variability plays a crucial role in the mid-latitudes. However, El Niño-Southern Oscillation (ENSO is still the main source of predictability in this region situated far away from the Pacific. Although the ENSO influence over tropical and extra-tropical areas is related to different physical mechanisms, in both regions this teleconnection seems to be non-stationary in time and modulated by multidecadal changes of the mean flow. Nowadays, long observational records (greater than 100 years and modeling projects (e.g., CMIP permit detecting non-stationarities in the influence of ENSO over the Atlantic basin, and further analyzing its potential mechanisms. The present article reviews the ENSO influence over the Atlantic region, paying special attention to the stability of this teleconnection over time and the possible modulators. Evidence is given that the ENSO–Atlantic teleconnection is weak over the North Atlantic. In this regard, the multidecadal ocean variability seems to modulate the presence of teleconnections, which can lead to important impacts of ENSO and to open windows of opportunity for seasonal predictability.
Fetterly, Kenneth A; Favazza, Christopher P
2016-08-07
Channelized Hotelling model observer (CHO) methods were developed to assess performance of an x-ray angiography system. The analytical methods included correction for known bias error due to finite sampling. Detectability indices ([Formula: see text]) corresponding to disk-shaped objects with diameters in the range 0.5-4 mm were calculated. Application of the CHO for variable detector target dose (DTD) in the range 6-240 nGy frame(-1) resulted in [Formula: see text] estimates which were as much as 2.9× greater than expected of a quantum limited system. Over-estimation of [Formula: see text] was presumed to be a result of bias error due to temporally variable non-stationary noise. Statistical theory which allows for independent contributions of 'signal' from a test object (o) and temporally variable non-stationary noise (ns) was developed. The theory demonstrates that the biased [Formula: see text] is the sum of the detectability indices associated with the test object [Formula: see text] and non-stationary noise ([Formula: see text]). Given the nature of the imaging system and the experimental methods, [Formula: see text] cannot be directly determined independent of [Formula: see text]. However, methods to estimate [Formula: see text] independent of [Formula: see text] were developed. In accordance with the theory, [Formula: see text] was subtracted from experimental estimates of [Formula: see text], providing an unbiased estimate of [Formula: see text]. Estimates of [Formula: see text] exhibited trends consistent with expectations of an angiography system that is quantum limited for high DTD and compromised by detector electronic readout noise for low DTD conditions. Results suggest that these methods provide [Formula: see text] estimates which are accurate and precise for [Formula: see text]. Further, results demonstrated that the source of bias was detector electronic readout noise. In summary, this work presents theory and methods to test for the
Directory of Open Access Journals (Sweden)
Deborah A Striegel
2015-08-01
Full Text Available Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets.
Striegel, Deborah A; Hara, Manami; Periwal, Vipul
2015-08-01
Pancreatic islets of Langerhans consist of endocrine cells, primarily α, β and δ cells, which secrete glucagon, insulin, and somatostatin, respectively, to regulate plasma glucose. β cells form irregular locally connected clusters within islets that act in concert to secrete insulin upon glucose stimulation. Due to the central functional significance of this local connectivity in the placement of β cells in an islet, it is important to characterize it quantitatively. However, quantification of the seemingly stochastic cytoarchitecture of β cells in an islet requires mathematical methods that can capture topological connectivity in the entire β-cell population in an islet. Graph theory provides such a framework. Using large-scale imaging data for thousands of islets containing hundreds of thousands of cells in human organ donor pancreata, we show that quantitative graph characteristics differ between control and type 2 diabetic islets. Further insight into the processes that shape and maintain this architecture is obtained by formulating a stochastic theory of β-cell rearrangement in whole islets, just as the normal equilibrium distribution of the Ornstein-Uhlenbeck process can be viewed as the result of the interplay between a random walk and a linear restoring force. Requiring that rearrangements maintain the observed quantitative topological graph characteristics strongly constrained possible processes. Our results suggest that β-cell rearrangement is dependent on its connectivity in order to maintain an optimal cluster size in both normal and T2D islets.
HMM filtering and parameter estimation of an electricity spot price model
International Nuclear Information System (INIS)
Erlwein, Christina; Benth, Fred Espen; Mamon, Rogemar
2010-01-01
In this paper we develop a model for electricity spot price dynamics. The spot price is assumed to follow an exponential Ornstein-Uhlenbeck (OU) process with an added compound Poisson process. In this way, the model allows for mean-reversion and possible jumps. All parameters are modulated by a hidden Markov chain in discrete time. They are able to switch between different economic regimes representing the interaction of various factors. Through the application of reference probability technique, adaptive filters are derived, which in turn, provide optimal estimates for the state of the Markov chain and related quantities of the observation process. The EM algorithm is applied to find optimal estimates of the model parameters in terms of the recursive filters. We implement this self-calibrating model on a deseasonalised series of daily spot electricity prices from the Nordic exchange Nord Pool. On the basis of one-step ahead forecasts, we found that the model is able to capture the empirical characteristics of Nord Pool spot prices. (author)
Level crossings and excess times due to a superposition of uncorrelated exponential pulses
Theodorsen, A.; Garcia, O. E.
2018-01-01
A well-known stochastic model for intermittent fluctuations in physical systems is investigated. The model is given by a superposition of uncorrelated exponential pulses, and the degree of pulse overlap is interpreted as an intermittency parameter. Expressions for excess time statistics, that is, the rate of level crossings above a given threshold and the average time spent above the threshold, are derived from the joint distribution of the process and its derivative. Limits of both high and low intermittency are investigated and compared to previously known results. In the case of a strongly intermittent process, the distribution of times spent above threshold is obtained analytically. This expression is verified numerically, and the distribution of times above threshold is explored for other intermittency regimes. The numerical simulations compare favorably to known results for the distribution of times above the mean threshold for an Ornstein-Uhlenbeck process. This contribution generalizes the excess time statistics for the stochastic model, which find applications in a wide diversity of natural and technological systems.
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Maejima, M.; Sato, K.
2006-01-01
The class of distributions on R generated by convolutions of Γ-distributions and the class generated by convolutions of mixtures of exponential distributions are generalized to higher dimensions and denoted by T(Rd) and B(Rd) . From the Lévy process {Xt(μ)} on Rd with distribution μ at t=1, Υ...... divisible distributions and of self-decomposable distributions on Rd , respectively. The relations with the mapping Φ from μ to the distribution at each time of the stationary process of Ornstein-Uhlenbeck type with background driving Lévy process {Xt(μ)} are studied. Developments of these results......(μ) is defined as the distribution of the stochastic integral ∫01log(1/t)dXt(μ) . This mapping is a generalization of the mapping Υ introduced by Barndorff-Nielsen and Thorbjørnsen in one dimension. It is proved that ϒ(ID(Rd))=B(Rd) and ϒ(L(Rd))=T(Rd) , where ID(Rd) and L(Rd) are the classes of infinitely...
Coupling regularizes individual units in noisy populations
International Nuclear Information System (INIS)
Ly Cheng; Ermentrout, G. Bard
2010-01-01
The regularity of a noisy system can modulate in various ways. It is well known that coupling in a population can lower the variability of the entire network; the collective activity is more regular. Here, we show that diffusive (reciprocal) coupling of two simple Ornstein-Uhlenbeck (O-U) processes can regularize the individual, even when it is coupled to a noisier process. In cellular networks, the regularity of individual cells is important when a select few play a significant role. The regularizing effect of coupling surprisingly applies also to general nonlinear noisy oscillators. However, unlike with the O-U process, coupling-induced regularity is robust to different kinds of coupling. With two coupled noisy oscillators, we derive an asymptotic formula assuming weak noise and coupling for the variance of the period (i.e., spike times) that accurately captures this effect. Moreover, we find that reciprocal coupling can regularize the individual period of higher dimensional oscillators such as the Morris-Lecar and Brusselator models, even when coupled to noisier oscillators. Coupling can have a counterintuitive and beneficial effect on noisy systems. These results have implications for the role of connectivity with noisy oscillators and the modulation of variability of individual oscillators.
International Nuclear Information System (INIS)
Roulier, Remy; Humeau, Anne; Flatley, Thomas P; Abraham, Pierre
2005-01-01
A significant transient increase in laser Doppler flowmetry (LDF) signals is observed in response to a local and progressive cutaneous pressure application on healthy subjects. This reflex may be impaired in diabetic patients. The work presents a comparison between two signal processing methods that provide a clarification of this phenomenon. Analyses by the scalogram and the Hilbert-Huang transform (HHT) of LDF signals recorded at rest and during a local and progressive cutaneous pressure application are performed on healthy and type 1 diabetic subjects. Three frequency bands, corresponding to myogenic, neurogenic and endothelial related metabolic activities, are studied at different time intervals in order to take into account the dynamics of the phenomenon. The results show that both the scalogram and the HHT methods lead to the same conclusions concerning the comparisons of the myogenic, neurogenic and endothelial related metabolic activities-during the progressive pressure and at rest-in healthy and diabetic subjects. However, the HHT shows more details that may be obscured by the scalogram. Indeed, the non-locally adaptative limitations of the scalogram can remove some definition from the data. These results may improve knowledge on the above-mentioned reflex as well as on non-stationary biomedical signal processing methods
Equivalence of interest rate models and lattice gases.
Pirjol, Dan
2012-04-01
We consider the class of short rate interest rate models for which the short rate is proportional to the exponential of a Gaussian Markov process x(t) in the terminal measure r(t)=a(t)exp[x(t)]. These models include the Black-Derman-Toy and Black-Karasinski models in the terminal measure. We show that such interest rate models are equivalent to lattice gases with attractive two-body interaction, V(t(1),t(2))=-Cov[x(t(1)),x(t(2))]. We consider in some detail the Black-Karasinski model with x(t) as an Ornstein-Uhlenbeck process, and show that it is similar to a lattice gas model considered by Kac and Helfand, with attractive long-range two-body interactions, V(x,y)=-α(e(-γ|x-y|)-e(-γ(x+y))). An explicit solution for the model is given as a sum over the states of the lattice gas, which is used to show that the model has a phase transition similar to that found previously in the Black-Derman-Toy model in the terminal measure.
Bilayer graphene lattice-layer entanglement in the presence of non-Markovian phase noise
Bittencourt, Victor A. S. V.; Blasone, Massimo; Bernardini, Alex E.
2018-03-01
The evolution of single particle excitations of bilayer graphene under effects of non-Markovian noise is described with focus on the decoherence process of lattice-layer (LL) maximally entangled states. Once the noiseless dynamics of an arbitrary initial state is identified by the correspondence between the tight-binding Hamiltonian for the AB-stacked bilayer graphene and the Dirac equation—which includes pseudovectorlike and tensorlike field interactions—the noisy environment is described as random fluctuations on bias voltage and mass terms. The inclusion of noisy dynamics reproduces the Ornstein-Uhlenbeck processes: A non-Markovian noise model with a well-defined Markovian limit. Considering that an initial amount of entanglement shall be dissipated by the noise, two profiles of dissipation are identified. On one hand, for eigenstates of the noiseless Hamiltonian, deaths and revivals of entanglement are identified along the oscillation pattern for long interaction periods. On the other hand, for departing LL Werner and Cat states, the entanglement is suppressed although, for both cases, some identified memory effects compete with the pure noise-induced decoherence in order to preserve the the overall profile of a given initial state.
Mulder, Willem H; Crawford, Forrest W
2015-01-07
Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.
Framework based on communicability and flow to analyze complex network dynamics
Gilson, M.; Kouvaris, N. E.; Deco, G.; Zamora-López, G.
2018-05-01
Graph theory constitutes a widely used and established field providing powerful tools for the characterization of complex networks. The intricate topology of networks can also be investigated by means of the collective dynamics observed in the interactions of self-sustained oscillations (synchronization patterns) or propagationlike processes such as random walks. However, networks are often inferred from real-data-forming dynamic systems, which are different from those employed to reveal their topological characteristics. This stresses the necessity for a theoretical framework dedicated to the mutual relationship between the structure and dynamics in complex networks, as the two sides of the same coin. Here we propose a rigorous framework based on the network response over time (i.e., Green function) to study interactions between nodes across time. For this purpose we define the flow that describes the interplay between the network connectivity and external inputs. This multivariate measure relates to the concepts of graph communicability and the map equation. We illustrate our theory using the multivariate Ornstein-Uhlenbeck process, which describes stable and non-conservative dynamics, but the formalism can be adapted to other local dynamics for which the Green function is known. We provide applications to classical network examples, such as small-world ring and hierarchical networks. Our theory defines a comprehensive framework that is canonically related to directed and weighted networks, thus paving a way to revise the standards for network analysis, from the pairwise interactions between nodes to the global properties of networks including community detection.
Front Propagation in Stochastic Neural Fields
Bressloff, Paul C.
2012-01-01
We analyze the effects of extrinsic multiplicative noise on front propagation in a scalar neural field with excitatory connections. Using a separation of time scales, we represent the fluctuating front in terms of a diffusive-like displacement (wandering) of the front from its uniformly translating position at long time scales, and fluctuations in the front profile around its instantaneous position at short time scales. One major result of our analysis is a comparison between freely propagating fronts and fronts locked to an externally moving stimulus. We show that the latter are much more robust to noise, since the stochastic wandering of the mean front profile is described by an Ornstein-Uhlenbeck process rather than a Wiener process, so that the variance in front position saturates in the long time limit rather than increasing linearly with time. Finally, we consider a stochastic neural field that supports a pulled front in the deterministic limit, and show that the wandering of such a front is now subdiffusive. © 2012 Society for Industrial and Applied Mathematics.
Dynamic analysis of trapping and escaping in dual beam optical trap
Li, Wenqiang; Hu, Huizhu; Su, Heming; Li, Zhenggang; Shen, Yu
2016-10-01
In this paper, we simulate the dynamic movement of a dielectric sphere in optical trap. This dynamic analysis can be used to calibrate optical forces, increase trapping efficiency and measure viscous coefficient of surrounding medium. Since an accurate dynamic analysis is based on a detailed force calculation, we calculate all forces a sphere receives. We get the forces of dual-beam gradient radiation pressure on a micron-sized dielectric sphere in the ray optics regime and utilize Einstein-Ornstein-Uhlenbeck to deal with its Brownian motion forces. Hydrodynamic viscous force also exists when the sphere moves in liquid. Forces from buoyance and gravity are also taken into consideration. Then we simulate trajectory of a sphere when it is subject to all these forces in a dual optical trap. From our dynamic analysis, the sphere can be trapped at an equilibrium point in static water, although it permanently fluctuates around the equilibrium point due to thermal effects. We go a step further to analyze the effects of misalignment of two optical traps. Trapping and escaping phenomena of the sphere in flowing water are also simulated. In flowing water, the sphere is dragged away from the equilibrium point. This dragging distance increases with the decrease of optical power, which results in escaping of the sphere with optical power below a threshold. In both trapping and escaping process we calculate the forces and position of the sphere. Finally, we analyze a trapping region in dual optical tweezers.
Wittmann, René; Maggi, C.; Sharma, A.; Scacchi, A.; Brader, J. M.; Marini Bettolo Marconi, U.
2017-11-01
The equations of motion of active systems can be modeled in terms of Ornstein-Uhlenbeck processes (OUPs) with appropriate correlators. For further theoretical studies, these should be approximated to yield a Markovian picture for the dynamics and a simplified steady-state condition. We perform a comparative study of the unified colored noise approximation (UCNA) and the approximation scheme by Fox recently employed within this context. We review the approximations necessary to define effective interaction potentials in the low-density limit and study the conditions for which these represent the behavior observed in two-body simulations for the OUPs model and active Brownian particles. The demonstrated limitations of the theory for potentials with a negative slope or curvature can be qualitatively corrected by a new empirical modification. In general, we find that in the presence of translational white noise the Fox approach is more accurate. Finally, we examine an alternative way to define a force-balance condition in the limit of small activity.
International Nuclear Information System (INIS)
Wu, Wei; Wang, Jin
2014-01-01
We have established a general non-equilibrium thermodynamic formalism consistently applicable to both spatially homogeneous and, more importantly, spatially inhomogeneous systems, governed by the Langevin and Fokker-Planck stochastic dynamics with multiple state transition mechanisms, using the potential-flux landscape framework as a bridge connecting stochastic dynamics with non-equilibrium thermodynamics. A set of non-equilibrium thermodynamic equations, quantifying the relations of the non-equilibrium entropy, entropy flow, entropy production, and other thermodynamic quantities, together with their specific expressions, is constructed from a set of dynamical decomposition equations associated with the potential-flux landscape framework. The flux velocity plays a pivotal role on both the dynamic and thermodynamic levels. On the dynamic level, it represents a dynamic force breaking detailed balance, entailing the dynamical decomposition equations. On the thermodynamic level, it represents a thermodynamic force generating entropy production, manifested in the non-equilibrium thermodynamic equations. The Ornstein-Uhlenbeck process and more specific examples, the spatial stochastic neuronal model, in particular, are studied to test and illustrate the general theory. This theoretical framework is particularly suitable to study the non-equilibrium (thermo)dynamics of spatially inhomogeneous systems abundant in nature. This paper is the second of a series
Scales, Jeffrey A; Butler, Marguerite A
2016-01-01
Despite the complexity of nature, most comparative studies of phenotypic evolution consider selective pressures in isolation. When competing pressures operate on the same system, it is commonly expected that trade-offs will occur that will limit the evolution of phenotypic diversity, however, it is possible that interactions among selective pressures may promote diversity instead. We explored the evolution of locomotor performance in lizards in relation to possible selective pressures using the Ornstein-Uhlenbeck process. Here, we show that a combination of selection based on foraging mode and predator escape is required to explain variation in performance phenotypes. Surprisingly, habitat use contributed little explanatory power. We find that it is possible to evolve very different abilities in performance which were previously thought to be tightly correlated, supporting a growing literature that explores the many-to-one mapping of morphological design. Although we generally find the expected trade-off between maximal exertion and speed, this relationship surprisingly disappears when species experience selection for both performance types. We conclude that functional integration need not limit adaptive potential, and that an integrative approach considering multiple major influences on a phenotype allows a more complete understanding of adaptation and the evolution of diversity. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.
The best of both worlds: Phylogenetic eigenvector regression and mapping
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José Alexandre Felizola Diniz Filho
2015-09-01
Full Text Available Eigenfunction analyses have been widely used to model patterns of autocorrelation in time, space and phylogeny. In a phylogenetic context, Diniz-Filho et al. (1998 proposed what they called Phylogenetic Eigenvector Regression (PVR, in which pairwise phylogenetic distances among species are submitted to a Principal Coordinate Analysis, and eigenvectors are then used as explanatory variables in regression, correlation or ANOVAs. More recently, a new approach called Phylogenetic Eigenvector Mapping (PEM was proposed, with the main advantage of explicitly incorporating a model-based warping in phylogenetic distance in which an Ornstein-Uhlenbeck (O-U process is fitted to data before eigenvector extraction. Here we compared PVR and PEM in respect to estimated phylogenetic signal, correlated evolution under alternative evolutionary models and phylogenetic imputation, using simulated data. Despite similarity between the two approaches, PEM has a slightly higher prediction ability and is more general than the original PVR. Even so, in a conceptual sense, PEM may provide a technique in the best of both worlds, combining the flexibility of data-driven and empirical eigenfunction analyses and the sounding insights provided by evolutionary models well known in comparative analyses.
Geometric capture and escape of a microswimmer colliding with an obstacle.
Spagnolie, Saverio E; Moreno-Flores, Gregorio R; Bartolo, Denis; Lauga, Eric
2015-05-07
Motivated by recent experiments, we consider the hydrodynamic capture of a microswimmer near a stationary spherical obstacle. Simulations of model equations show that a swimmer approaching a small spherical colloid is simply scattered. In contrast, when the colloid is larger than a critical size it acts as a passive trap: the swimmer is hydrodynamically captured along closed trajectories and endlessly orbits around the colloidal sphere. In order to gain physical insight into this hydrodynamic scattering problem, we address it analytically. We provide expressions for the critical trapping radius, the depth of the "basin of attraction," and the scattering angle, which show excellent agreement with our numerical findings. We also demonstrate and rationalize the strong impact of swimming-flow symmetries on the trapping efficiency. Finally, we give the swimmer an opportunity to escape the colloidal traps by considering the effects of Brownian, or active, diffusion. We show that in some cases the trapping time is governed by an Ornstein-Uhlenbeck process, which results in a trapping time distribution that is well-approximated as inverse-Gaussian. The predictions again compare very favorably with the numerical simulations. We envision applications of the theory to bioremediation, microorganism sorting techniques, and the study of bacterial populations in heterogeneous or porous environments.
Dynamic Looping of a Free-Draining Polymer
Energy Technology Data Exchange (ETDEWEB)
Ye, Felix X. -F.; Stinis, Panos; Qian, Hong
2018-01-11
Here, we revisit the celebrated Wilemski--Fixman (WF) treatment for the looping time of a free-draining polymer. The WF theory introduces a sink term into the Fokker--Planck equation for the $3(N+1)$-dimensional Ornstein--Uhlenbeck process of polymer dynamics, which accounts for the appropriate boundary condition due to the formation of a loop. The assumption for WF theory is considerably relaxed. A perturbation method approach is developed that justifies and generalizes the previous results using either a delta sink or a Heaviside sink. For both types of sinks, we show that under the condition of a small dimensionless $\\epsilon$, the ratio of capture radius to the Kuhn length, we are able to systematically produce all known analytical and asymptotic results obtained by other methods. This includes most notably the transition regime between the $N^2$ scaling of Doi, and $N\\sqrt{N}/\\epsilon$ scaling of Szabo, Schulten, and Schulten. The mathematical issue at play is the nonuniform convergence of $\\epsilon\\to 0$ and $N\\to\\infty$, the latter being an inherent part of the theory of a Gaussian polymer. Our analysis yields a novel term in the analytical expression for the looping time with small $\\epsilon$, which was previously unknown. Monte Carlo numerical simulations corroborate the analytical findings. The systematic method developed here can be applied to other systems modeled by multidimensional Smoluchowski equations.
LNG as a strategy to establish developing countries' gas markets: The Brazilian case
International Nuclear Information System (INIS)
Alberto Rechelo Neto, Carlos; Sauer, Ildo Luis
2006-01-01
This paper aims to evaluate, from a Brazilian case study, if the natural gas trade can be viewed as a good opportunity for developing countries located geographically close to Western Europe and North America gas markets. Initially, the paper presents an overview of the Brazilian natural gas industry and evaluates the balance between supply and demand in each main region of Brazil. Then, it analyzes the evolution of the international gas trade, which is expected to increase rapidly (LNG particularly). Finally, the paper analyses the financial viability of the Brazilian LNG project in a context of high volatility of natural gas prices in the international market. To take this uncertainty into account, North-American natural gas prices are modelled according to the ORNSTEIN-UHLENBECK process (with EIA data over the period 1985-2003). By using an approach based on Monte-Carlo simulations and under the assumption that imports are guaranteed since the North American gas price would be higher than the breakeven of the Brazilian project, the model aims to test the hypothesis that export can promote the development of the Brazilian Northeastern gas market. LNG project is here compared to the Petrobras pipelines project, which is considered as the immediate solution for the Northeastern gas shortage. As a conclusion, this study shows that the LNG export will be vulnerable to the risks associated to the natural gas prices volatility observed on the international market
Seyrich, Maximilian; Sornette, Didier
2016-04-01
We present a plausible micro-founded model for the previously postulated power law finite time singular form of the crash hazard rate in the Johansen-Ledoit-Sornette (JLS) model of rational expectation bubbles. The model is based on a percolation picture of the network of traders and the concept that clusters of connected traders share the same opinion. The key ingredient is the notion that a shift of position from buyer to seller of a sufficiently large group of traders can trigger a crash. This provides a formula to estimate the crash hazard rate by summation over percolation clusters above a minimum size of a power sa (with a>1) of the cluster sizes s, similarly to a generalized percolation susceptibility. The power sa of cluster sizes emerges from the super-linear dependence of group activity as a function of group size, previously documented in the literature. The crash hazard rate exhibits explosive finite time singular behaviors when the control parameter (fraction of occupied sites, or density of traders in the network) approaches the percolation threshold pc. Realistic dynamics are generated by modeling the density of traders on the percolation network by an Ornstein-Uhlenbeck process, whose memory controls the spontaneous excursion of the control parameter close to the critical region of bubble formation. Our numerical simulations recover the main stylized properties of the JLS model with intermittent explosive super-exponential bubbles interrupted by crashes.
Simplified rotor load models and fatigue damage estimates for offshore wind turbines.
Muskulus, M
2015-02-28
The aim of rotor load models is to characterize and generate the thrust loads acting on an offshore wind turbine. Ideally, the rotor simulation can be replaced by time series from a model with a few parameters and state variables only. Such models are used extensively in control system design and, as a potentially new application area, structural optimization of support structures. Different rotor load models are here evaluated for a jacket support structure in terms of fatigue lifetimes of relevant structural variables. All models were found to be lacking in accuracy, with differences of more than 20% in fatigue load estimates. The most accurate models were the use of an effective thrust coefficient determined from a regression analysis of dynamic thrust loads, and a novel stochastic model in state-space form. The stochastic model explicitly models the quasi-periodic components obtained from rotational sampling of turbulent fluctuations. Its state variables follow a mean-reverting Ornstein-Uhlenbeck process. Although promising, more work is needed on how to determine the parameters of the stochastic model and before accurate lifetime predictions can be obtained without comprehensive rotor simulations. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Stochastic particle acceleration and statistical closures
International Nuclear Information System (INIS)
Dimits, A.M.; Krommes, J.A.
1985-10-01
In a recent paper, Maasjost and Elsasser (ME) concluded, from the results of numerical experiments and heuristic arguments, that the Bourret and the direct-interaction approximation (DIA) are ''of no use in connection with the stochastic acceleration problem'' because (1) their predictions were equivalent to that of the simpler Fokker-Planck (FP) theory, and (2) either all or none of the closures were in good agreement with the data. Here some analytically tractable cases are studied and used to test the accuracy of these closures. The cause of the discrepancy (2) is found to be the highly non-Gaussian nature of the force used by ME, a point not stressed by them. For the case where the force is a position-independent Ornstein-Uhlenbeck (i.e., Gaussian) process, an effective Kubo number K can be defined. For K << 1 an FP description is adequate, and conclusion (1) of ME follows; however, for K greater than or equal to 1 the DIA behaves much better qualitatively than the other two closures. For the non-Gaussian stochastic force used by ME, all common approximations fail, in agreement with (2)
Linear response and correlation of a self-propelled particle in the presence of external fields
Caprini, Lorenzo; Marini Bettolo Marconi, Umberto; Vulpiani, Angelo
2018-03-01
We study the non-equilibrium properties of non interacting active Ornstein-Uhlenbeck particles (AOUP) subject to an external nonuniform field using a Fokker-Planck approach with a focus on the linear response and time-correlation functions. In particular, we compare different methods to compute these functions including the unified colored noise approximation (UCNA). The AOUP model, described by the position of the particle and the active force acting on it, is usually mapped into a Markovian process, describing the motion of a fictitious passive particle in terms of its position and velocity, where the effect of the activity is transferred into a position-dependent friction. We show that the form of the response function of the AOUP depends on whether we put the perturbation on the position and keep unperturbed the active force in the original variables or perturb the position and maintain unperturbed the velocity in the transformed variables. Indeed, as a result of the change of variables the perturbation on the position becomes a perturbation both on the position and on the fictitious velocity. We test these predictions by considering the response for three types of convex potentials: quadratic, quartic and double-well potential. Moreover, by comparing the response of the AOUP model with the corresponding response of the UCNA model we conclude that although the stationary properties are fairly well approximated by the UCNA, the non equilibrium properties are not, an effect which is not negligible when the persistence time is large.
EDITORIAL: The nonstationary Casimir effect and quantum systems with moving boundaries
Barton, Gabriel; Dodonov, Victor V.; Man'ko, Vladimir I.
2005-03-01
This topical issue of Journal of Optics B: Quantum and Semiclassical Optics contains 16 contributions devoted to quantum systems with moving boundaries. In a broad sense, the papers continue the studies opened exactly 100 years ago by Einstein in his seminal work on the electrodynamics of moving bodies and the quantum nature of light. Another jubilee which we wish to celebrate by launching this issue is the 80th anniversary of the publication of two papers, where the first solutions of the classical Maxwell equations in a one-dimensional cavity with moving boundaries were obtained, by T H Havelock (1924 Some dynamical illustrations of the pressure of radiation and of adiabatic invariance Phil. Mag. 47 754-71) and by E L Nicolai (1925 On a dynamical illustration of the pressure of radiation Phil. Mag. 49 171-7). As was shown by Einstein, studying the fluctuations of the electromagnetic field inevitably leads one to its quantum (corpuscular) nature. Many papers in this issue deal with problems where moving boundaries produce parametric excitation of vacuum fluctuations of the field, which could result in several different observable effects, like the modification of the famous Casimir force, or the creation of real quanta from the vacuum. It is worth emphasizing that these phenomena, frequently referred to as nonstationary (or dynamical) Casimir effects, are no longer the province only of pure theorists: some experimental groups have already started long-term work aimed at observing such effects in the laboratory. Of course, many difficult problems remain to be resolved before this dream becomes reality. Several papers here show both important progress in this direction, and possible difficulties still to be tackled. Problems that have been considered include, in particular, decoherence, entanglement, and the roles of geometry and polarization. Other papers deal with fundamental problems like the Unruh effect, the interaction of accelerated relativistic atoms with
Sun, Qiaohong; Miao, Chiyuan; Qiao, Yuanyuan; Duan, Qingyun
2017-12-01
The El Niño-Southern Oscillation (ENSO) and local temperature are important drivers of extreme precipitation. Understanding the impact of ENSO and temperature on the risk of extreme precipitation over global land will provide a foundation for risk assessment and climate-adaptive design of infrastructure in a changing climate. In this study, nonstationary generalized extreme value distributions were used to model extreme precipitation over global land for the period 1979-2015, with ENSO indicator and temperature as covariates. Risk factors were estimated to quantify the contrast between the influence of different ENSO phases and temperature. The results show that extreme precipitation is dominated by ENSO over 22% of global land and by temperature over 26% of global land. With a warming climate, the risk of high-intensity daily extreme precipitation increases at high latitudes but decreases in tropical regions. For ENSO, large parts of North America, southern South America, and southeastern and northeastern China are shown to suffer greater risk in El Niño years, with more than double the chance of intense extreme precipitation in El Niño years compared with La Niña years. Moreover, regions with more intense precipitation are more sensitive to ENSO. Global climate models were used to investigate the changing relationship between extreme precipitation and the covariates. The risk of extreme, high-intensity precipitation increases across high latitudes of the Northern Hemisphere but decreases in middle and lower latitudes under a warming climate scenario, and will likely trigger increases in severe flooding and droughts across the globe. However, there is some uncertainties associated with the influence of ENSO on predictions of future extreme precipitation, with the spatial extent and risk varying among the different models.
Kreppel, Katharina S; Caminade, Cyril; Telfer, Sandra; Rajerison, Minoarison; Rahalison, Lila; Morse, Andy; Baylis, Matthew
2014-10-01
Plague, a zoonosis caused by Yersinia pestis, is found in Asia and the Americas, but predominantly in Africa, with the island of Madagascar reporting almost one third of human cases worldwide. Plague's occurrence is affected by local climate factors which in turn are influenced by large-scale climate phenomena such as the El Niño Southern Oscillation (ENSO). The effects of ENSO on regional climate are often enhanced or reduced by a second large-scale climate phenomenon, the Indian Ocean Dipole (IOD). It is known that ENSO and the IOD interact as drivers of disease. Yet the impacts of these phenomena in driving plague dynamics via their effect on regional climate, and specifically contributing to the foci of transmission on Madagascar, are unknown. Here we present the first analysis of the effects of ENSO and IOD on plague in Madagascar. We use a forty-eight year monthly time-series of reported human plague cases from 1960 to 2008. Using wavelet analysis, we show that over the last fifty years there have been complex non-stationary associations between ENSO/IOD and the dynamics of plague in Madagascar. We demonstrate that ENSO and IOD influence temperature in Madagascar and that temperature and plague cycles are associated. The effects on plague appear to be mediated more by temperature, but precipitation also undoubtedly influences plague in Madagascar. Our results confirm a relationship between plague anomalies and an increase in the intensity of ENSO events and precipitation. This work widens the understanding of how climate factors acting over different temporal scales can combine to drive local disease dynamics. Given the association of increasing ENSO strength and plague anomalies in Madagascar it may in future be possible to forecast plague outbreaks in Madagascar. The study gives insight into the complex and changing relationship between climate factors and plague in Madagascar.
Haguma, D.; Leconte, R.
2017-12-01
Spatial and temporal water resources variability are associated with large-scale pressure and circulation anomalies known as teleconnections that influence the pattern of the atmospheric circulation. Teleconnection indices have been used successfully to forecast streamflow in short term. However, in some watersheds, classical methods cannot establish relationships between seasonal streamflow and teleconnection indices because of weak correlation. In this study, machine learning algorithms have been applied for seasonal streamflow forecast using teleconnection indices. Machine learning offers an alternative to classical methods to address the non-linear relationship between streamflow and teleconnection indices the context non-stationary climate. Two machine learning algorithms, random forest (RF) and support vector machine (SVM), with teleconnection indices associated with North American climatology, have been used to forecast inflows for one and two leading seasons for the Romaine River and Manicouagan River watersheds, located in Quebec, Canada. The indices are Pacific-North America (PNA), North Atlantic Oscillation (NAO), El Niño-Southern Oscillation (ENSO), Arctic Oscillation (AO) and Pacific Decadal Oscillation (PDO). The results showed that the machine learning algorithms have an important predictive power for seasonal streamflow for one and two leading seasons. The RF performed better for training and SVM generally have better results with high predictive capability for testing. The RF which is an ensemble method, allowed to assess the uncertainty of the forecast. The integration of teleconnection indices responds to the seasonal forecast of streamflow in the conditions of the non-stationarity the climate, although the teleconnection indices have a weak correlation with streamflow.
Laabidi, Ezzeddine; Bouhlila, Rachida
2015-07-01
In the last few decades, hydrogeochemical problems have benefited from the strong interest in numerical modeling. One of the most recognized hydrogeochemical problems is the dissolution of the calcite in the mixing zone below limestone coastal aquifer. In many works, this problem has been modeled using a coupling algorithm between a density-dependent flow model and a geochemical model. A related difficulty is that, because of the high nonlinearity of the coupled set of equations, high computational effort is needed. During calcite dissolution, an increase in permeability can be identified, which can induce an increase in the penetration of the seawater into the aquifer. The majority of the previous studies used a fully coupled reactive transport model in order to model such problem. Romanov and Dreybrodt (J Hydrol 329:661-673, 2006) have used an alternative approach to quantify the porosity evolution in mixing zone below coastal carbonate aquifer at steady state. This approach is based on the analytic solution presented by Phillips (1991) in his book Flow and Reactions in Permeable Rock, which shows that it is possible to decouple the complex set of equation. This equation is proportional to the square of the salinity gradient, which can be calculated using a density driven flow code and to the reaction rate that can be calculated using a geochemical code. In this work, this equation is used in nonstationary step-by-step regime. At each time step, the quantity of the dissolved calcite is quantified, the change of porosity is calculated, and the permeability is updated. The reaction rate, which is the second derivate of the calcium equilibrium concentration in the equation, is calculated using the PHREEQC code (Parkhurst and Apello 1999). This result is used in GEODENS (Bouhlila 1999; Bouhlila and Laabidi 2008) to calculate change of the porosity after calculating the salinity gradient. For the next time step, the same protocol is used but using the updated porosity
Statistical downscaling of rainfall: a non-stationary and multi-resolution approach
Rashid, Md. Mamunur; Beecham, Simon; Chowdhury, Rezaul Kabir
2016-05-01
A novel downscaling technique is proposed in this study whereby the original rainfall and reanalysis variables are first decomposed by wavelet transforms and rainfall is modelled using the semi-parametric additive model formulation of Generalized Additive Model in Location, Scale and Shape (GAMLSS). The flexibility of the GAMLSS model makes it feasible as a framework for non-stationary modelling. Decomposition of a rainfall series into different components is useful to separate the scale-dependent properties of the rainfall as this varies both temporally and spatially. The study was conducted at the Onkaparinga river catchment in South Australia. The model was calibrated over the period 1960 to 1990 and validated over the period 1991 to 2010. The model reproduced the monthly variability and statistics of the observed rainfall well with Nash-Sutcliffe efficiency (NSE) values of 0.66 and 0.65 for the calibration and validation periods, respectively. It also reproduced well the seasonal rainfall over the calibration (NSE = 0.37) and validation (NSE = 0.69) periods for all seasons. The proposed model was better than the tradition modelling approach (application of GAMLSS to the original rainfall series without decomposition) at reproducing the time-frequency properties of the observed rainfall, and yet it still preserved the statistics produced by the traditional modelling approach. When downscaling models were developed with general circulation model (GCM) historical output datasets, the proposed wavelet-based downscaling model outperformed the traditional downscaling model in terms of reproducing monthly rainfall for both the calibration and validation periods.
Directory of Open Access Journals (Sweden)
Katharina S Kreppel
2014-10-01
Full Text Available Plague, a zoonosis caused by Yersinia pestis, is found in Asia and the Americas, but predominantly in Africa, with the island of Madagascar reporting almost one third of human cases worldwide. Plague's occurrence is affected by local climate factors which in turn are influenced by large-scale climate phenomena such as the El Niño Southern Oscillation (ENSO. The effects of ENSO on regional climate are often enhanced or reduced by a second large-scale climate phenomenon, the Indian Ocean Dipole (IOD. It is known that ENSO and the IOD interact as drivers of disease. Yet the impacts of these phenomena in driving plague dynamics via their effect on regional climate, and specifically contributing to the foci of transmission on Madagascar, are unknown. Here we present the first analysis of the effects of ENSO and IOD on plague in Madagascar.We use a forty-eight year monthly time-series of reported human plague cases from 1960 to 2008. Using wavelet analysis, we show that over the last fifty years there have been complex non-stationary associations between ENSO/IOD and the dynamics of plague in Madagascar. We demonstrate that ENSO and IOD influence temperature in Madagascar and that temperature and plague cycles are associated. The effects on plague appear to be mediated more by temperature, but precipitation also undoubtedly influences plague in Madagascar. Our results confirm a relationship between plague anomalies and an increase in the intensity of ENSO events and precipitation.This work widens the understanding of how climate factors acting over different temporal scales can combine to drive local disease dynamics. Given the association of increasing ENSO strength and plague anomalies in Madagascar it may in future be possible to forecast plague outbreaks in Madagascar. The study gives insight into the complex and changing relationship between climate factors and plague in Madagascar.
Wang, Kejing; Zhang, Yuan; An, Youzhi; Jing, Zhuoxin; Wang, Chao
2013-09-01
With the fast urbanization process, how does the vegetation environment change in one of the most economically developed metropolis, Shanghai in East China? To answer this question, there is a pressing demand to explore the non-stationary relationship between socio-economic conditions and vegetation across Shanghai. In this study, environmental data on vegetation cover, the Normalized Difference Vegetation Index (NDVI) derived from MODIS imagery in 2003 were integrated with socio-economic data to reflect the city's vegetative conditions at the census block group level. To explore regional variations in the relationship of vegetation and socio-economic conditions, Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR) models were applied to characterize mean NDVI against three independent socio-economic variables, an urban land use ratio, Gross Domestic Product (GDP) and population density. The study results show that a considerable distinctive spatial variation exists in the relationship for each model. The GWR model has superior effects and higher precision than the OLS model at the census block group scale. So, it is more suitable to account for local effects and geographical variations. This study also indicates that unreasonable excessive urbanization, together with non-sustainable economic development, has a negative influence of vegetation vigor for some neighborhoods in Shanghai.
Zhou, Peng; Peng, Zhike; Chen, Shiqian; Yang, Yang; Zhang, Wenming
2018-06-01
With the development of large rotary machines for faster and more integrated performance, the condition monitoring and fault diagnosis for them are becoming more challenging. Since the time-frequency (TF) pattern of the vibration signal from the rotary machine often contains condition information and fault feature, the methods based on TF analysis have been widely-used to solve these two problems in the industrial community. This article introduces an effective non-stationary signal analysis method based on the general parameterized time-frequency transform (GPTFT). The GPTFT is achieved by inserting a rotation operator and a shift operator in the short-time Fourier transform. This method can produce a high-concentrated TF pattern with a general kernel. A multi-component instantaneous frequency (IF) extraction method is proposed based on it. The estimation for the IF of every component is accomplished by defining a spectrum concentration index (SCI). Moreover, such an IF estimation process is iteratively operated until all the components are extracted. The tests on three simulation examples and a real vibration signal demonstrate the effectiveness and superiority of our method.
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Charles Onyutha
2017-10-01
Full Text Available Some of the problems in drought assessments are that: analyses tend to focus on coarse temporal scales, many of the methods yield skewed indices, a few terminologies are ambiguously used, and analyses comprise an implicit assumption that the observations come from a stationary process. To solve these problems, this paper introduces non-stationary frequency analyses of quantiles. How to use non-parametric rescaling to obtain robust indices that are not (or minimally skewed is also introduced. To avoid ambiguity, some concepts on, e.g., incidence, extremity, etc., were revisited through shift from monthly to daily time scale. Demonstrations on the introduced methods were made using daily flow and precipitation insufficiency (precipitation minus potential evapotranspiration from the Blue Nile basin in Africa. Results show that, when a significant trend exists in extreme events, stationarity-based quantiles can be far different from those when non-stationarity is considered. The introduced non-parametric indices were found to closely agree with the well-known standardized precipitation evapotranspiration indices in many aspects but skewness. Apart from revisiting some concepts, the advantages of the use of fine instead of coarse time scales in drought assessment were given. The links for obtaining freely downloadable tools on how to implement the introduced methods were provided.
Bartelmus, Walter; Chaari, Fakher; Zimroz, Radoslaw; Haddar, Mohamed
2012-01-01
Condition monitoring of machines in non-stationary operations (CMMNO) can be seen as the major challenge for research in the field of machinery diagnostics. Condition monitoring of machines in non-stationary operations is the title of the presented book and the title of the Conference held in Hammamet - Tunisia March 26 – 28, 2012. It is the second conference under this title, first took place in Wroclaw - Poland , March 2011. The subject CMMNO comes directly from industry needs and observation of real objects. Most monitored and diagnosed objects used in industry works in non-stationary operations condition. The non-stationary operations come from fulfillment of machinery tasks, for which they are designed for. All machinery used in different kind of mines, transport systems, vehicles like: cars, buses etc, helicopters, ships and battleships and so on work in non-stationary operations. The papers included in the book are shaped by the organizing board of the conference and authors of the papers. The papers...
Solving Dynamic Traveling Salesman Problem Using Dynamic Gaussian Process Regression
Directory of Open Access Journals (Sweden)
Stephen M. Akandwanaho
2014-01-01
Full Text Available This paper solves the dynamic traveling salesman problem (DTSP using dynamic Gaussian Process Regression (DGPR method. The problem of varying correlation tour is alleviated by the nonstationary covariance function interleaved with DGPR to generate a predictive distribution for DTSP tour. This approach is conjoined with Nearest Neighbor (NN method and the iterated local search to track dynamic optima. Experimental results were obtained on DTSP instances. The comparisons were performed with Genetic Algorithm and Simulated Annealing. The proposed approach demonstrates superiority in finding good traveling salesman problem (TSP tour and less computational time in nonstationary conditions.
Directory of Open Access Journals (Sweden)
Porshnev Sergey
2017-01-01
Full Text Available This work devoted to researching of mathematical model of non-stationary queuing system (NQS. Arrival rate in studied NQS λ(t is similar to rate which observed in practice in a real access control system of objects of mass events. Dependence of number of serviced requests from time was calculated. It is proven that the ratio value of served requests at the beginning of event to all served requests described by a deterministic function, depending on the average service rate μ¯$\\bar \\mu $ and the maximum value of the arrival rate function λ(t.
International Nuclear Information System (INIS)
Boiti, M.; Pempinelli, F.; Pogrebkov, A.K.; Polivanov, M.C.
1993-01-01
The resolvent operator of the linear problem is determined as the full Green function continued in the complex domain in two variables. An analog of the known Hilbert identity is derived. The authors demonstrate the role of this identity in the study of two-dimensional scattering. Considering the nonstationary Schroedinger equation as an example, it is shown that all types of solutions of the linear problem, as well as spectral data known in the literature, are given as specific values of this unique function - the resolvent function. A new form of the inverse problem is formulated. 7 refs
Fractional Poincaré inequalities for general measures
Mouhot, Clé ment; Russ, Emmanuel; Sire, Yannick
2011-01-01
on the fractional derivative in terms of a weight growing at infinity. The proof goes through the introduction of the generator of the Ornstein-Uhlenbeck semigroup and some careful estimates of its powers. To our knowledge this is the first proof of fractional
Meerson, Baruch; Fouxon, Itzhak; Vilenkin, Arkady
2008-02-01
We employ hydrodynamic equations to investigate nonstationary channel flows of freely cooling dilute gases of hard and smooth spheres with nearly elastic particle collisions. This work focuses on the regime where the sound travel time through the channel is much shorter than the characteristic cooling time of the gas. As a result, the gas pressure rapidly becomes almost homogeneous, while the typical Mach number of the flow drops well below unity. Eliminating the acoustic modes and employing Lagrangian coordinates, we reduce the hydrodynamic equations to a single nonlinear and nonlocal equation of a reaction-diffusion type. This equation describes a broad class of channel flows and, in particular, can follow the development of the clustering instability from a weakly perturbed homogeneous cooling state to strongly nonlinear states. If the heat diffusion is neglected, the reduced equation becomes exactly soluble, and the solution develops a finite-time density blowup. The blowup has the same local features at singularity as those exhibited by the recently found family of exact solutions of the full set of ideal hydrodynamic equations [I. Fouxon, Phys. Rev. E 75, 050301(R) (2007); I. Fouxon,Phys. Fluids 19, 093303 (2007)]. The heat diffusion, however, always becomes important near the attempted singularity. It arrests the density blowup and brings about previously unknown inhomogeneous cooling states (ICSs) of the gas, where the pressure continues to decay with time, while the density profile becomes time-independent. The ICSs represent exact solutions of the full set of granular hydrodynamic equations. Both the density profile of an ICS and the characteristic relaxation time toward it are determined by a single dimensionless parameter L that describes the relative role of the inelastic energy loss and heat diffusion. At L>1 the intermediate cooling dynamics proceeds as a competition between "holes": low-density regions of the gas. This competition resembles Ostwald
Hammouda, Imen; Mihoubi, Daoued
2017-12-01
This work deals with a numerical study of the response of a porcelain slab when subjected to convective drying in stationary and non-stationary conditions. The used model describes heat, mass, and momentum transfers is applied to an unsaturated viscoelastic medium described by a Maxwell model. The numerical code allows us to determine the effect of the surrounding air temperature on drying kinetics and on mechanical stress intensities. Von Mises stresses are analysed in order to foresee an eventual damage that may occur during drying. Simulation results for several temperatures in the range of [30 °C, 90 °C] shows that for the temperature from 30 °C to 60 °C, Von Mises stresses are always lower than the yield strength. But above 70 °C, Von Mises stresses are higher than the ultimate strength, and consequently there is a risk of crack at the end of the constant drying rate period. The idea proposed in this work is to integrate a reducing temperature phase when the predicted Von Mises stress intensity exceeds the admissible stress. Simulation results shows that a non-stationary convective drying (90-60 °C) allows us to optimize costs and quality by reducing the drying time and maintaining Von Mises stress values under the admissible stress.
International Nuclear Information System (INIS)
Verley, Gatien; Lacoste, David; Chétrite, Raphaël
2011-01-01
In this paper, we present a general derivation of a modified fluctuation-dissipation theorem (MFDT) valid near an arbitrary non-stationary state for a system obeying Markovian dynamics. We show that the method for deriving modified fluctuation-dissipation theorems near non-equilibrium stationary states used by Prost et al (2009 Phys. Rev. Lett. 103 090601) is generalizable to non-stationary states. This result follows from both standard linear response theory and from a transient fluctuation theorem, analogous to the Hatano–Sasa relation. We show that this modified fluctuation-dissipation theorem can be interpreted at the trajectory level using the notion of stochastic trajectory entropy, in a way which is similar to what has been done recently in the case of the MFDT near non-equilibrium steady states (NESS). We illustrate this framework with two solvable examples: the first example corresponds to a Brownian particle in a harmonic trap subjected to a quench of temperature and to a time-dependent stiffness; the second example is a classic model of coarsening systems, namely the 1D Ising model with Glauber dynamics
Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico
2009-03-01
We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.
Directory of Open Access Journals (Sweden)
Ermuratschii V.V.
2014-04-01
Full Text Available e paper presents a method of the approximate calculation of the non-stationary temperature field inside of thermal packed bed energy storages with feasible and latent heat. Applying thermoelectric models and computational methods in electrical engineering, the task of computing non-stationary heat transfer is resolved with respect to third type boundary conditions without applying differential equations of the heat transfer. For sub-volumes of the energy storage the method is executed iteratively in spatiotemporal domain. Single-body heating is modeled for each sub-volume, and modeling conditions are assumed to be identical for remained bod-ies, located in the same sub-volume. For each iteration step the boundary conditions will be represented by re-sults at the previous step. The fulfillment of the first law of thermodynamics for system “energy storage - body” is obtained by the iterative search of the mean temperature of the energy storage. Under variable boundary con-ditions the proposed method maybe applied to calculating temperature field inside of energy storages with packed beds consisted of solid material, liquid and phase-change material. The method may also be employed to compute transient, power and performance characteristics of packed bed energy storages.
Bi-spectrum based-EMD applied to the non-stationary vibration signals for bearing faults diagnosis.
Saidi, Lotfi; Ali, Jaouher Ben; Fnaiech, Farhat
2014-09-01
Empirical mode decomposition (EMD) has been widely applied to analyze vibration signals behavior for bearing failures detection. Vibration signals are almost always non-stationary since bearings are inherently dynamic (e.g., speed and load condition change over time). By using EMD, the complicated non-stationary vibration signal is decomposed into a number of stationary intrinsic mode functions (IMFs) based on the local characteristic time scale of the signal. Bi-spectrum, a third-order statistic, helps to identify phase coupling effects, the bi-spectrum is theoretically zero for Gaussian noise and it is flat for non-Gaussian white noise, consequently the bi-spectrum analysis is insensitive to random noise, which are useful for detecting faults in induction machines. Utilizing the advantages of EMD and bi-spectrum, this article proposes a joint method for detecting such faults, called bi-spectrum based EMD (BSEMD). First, original vibration signals collected from accelerometers are decomposed by EMD and a set of IMFs is produced. Then, the IMF signals are analyzed via bi-spectrum to detect outer race bearing defects. The procedure is illustrated with the experimental bearing vibration data. The experimental results show that BSEMD techniques can effectively diagnosis bearing failures. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Salomatov, V. V.; Puzyrev, E. M.; Salomatov, A. V.
2018-05-01
A class of nonlinear problems of nonstationary radiative-convective heat transfer under the microwave action with a small penetration depth is considered in a stabilized coolant flow in a circular channel. The solutions to these problems are obtained, using asymptotic procedures at the stages of nonstationary and stationary convective heat transfer on the heat-radiating channel surface. The nonstationary and stationary stages of the solution are matched, using the "longitudinal coordinate-time" characteristic. The approximate solutions constructed on such principles correlate reliably with the exact ones at the limiting values of the operation parameters, as well as with numerical and experimental data of other researchers. An important advantage of these solutions is that they allow the determination of the main regularities of the microwave and thermal radiation influence on convective heat transfer in a channel even before performing cumbersome calculations. It is shown that, irrespective of the heat exchange regime (nonstationary or stationary), the Nusselt number decreases and the rate of the surface temperature change increases with increase in the intensity of thermal action.
International Nuclear Information System (INIS)
Grunwald, G.; Mueller, E.
1983-08-01
For the computation of control rod oscillations in a flow channel we set up the differential equations for the non-stationary pressure distribution around the control elements which are coupled with the motion equations of the rods. The equation system is solved by means of a finite difference method. An example shows the efficiency of the numerical calculation procedure. (author)
Directory of Open Access Journals (Sweden)
Yue Hu
2018-01-01
Full Text Available Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST and multi-taper empirical wavelet transform (MTEWT is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR. As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.
The non-stationarity is a major concern for statistically downscaling climate change scenarios for impact assessment. This study is to evaluate whether a statistical downscaling method is fully applicable to generate daily precipitation under non-stationary conditions in a wide range of climatic zo...
Hu, Yue; Tu, Xiaotong; Li, Fucai; Meng, Guang
2018-01-07
Wind turbines usually operate under nonstationary conditions, such as wide-range speed fluctuation and time-varying load. Its critical component, the planetary gearbox, is prone to malfunction or failure, which leads to downtime and repair costs. Therefore, fault diagnosis and condition monitoring for the planetary gearbox in wind turbines is a vital research topic. Meanwhile, the signals measured by the vibration sensors mounted in the gearbox exhibit time-varying and nonstationary features. In this study, a novel time-frequency method based on high-order synchrosqueezing transform (SST) and multi-taper empirical wavelet transform (MTEWT) is proposed for the wind turbine planetary gearbox under nonstationary conditions. The high-order SST uses accurate instantaneous frequency approximations to obtain a sharper time-frequency representation (TFR). As the acquired signal consists of many components, like the meshing and rotating components of the gear and bearing, the fault component may be masked by other unrelated components. The MTEWT is used to separate the fault feature from the masking components. A variety of experimental signals of the wind turbine planetary gearbox under nonstationary conditions have been analyzed to demonstrate the effectiveness and robustness of the proposed method. Results show that the proposed method is effective in diagnosing both gear and bearing faults.
Climate change and flood hazard: Evaluation of the SCHADEX methodology in a non-stationary context
International Nuclear Information System (INIS)
Brigode, Pierre
2013-01-01
Since 2006, Electricite de France (EDF) applies a new hydro-climatological approach of extreme rainfall and flood predetermination - the SCHADEX method - for the design of dam spillways. In a context of potential increase of extreme event intensity and frequency due to climate change, the use of the SCHADEX method in non-stationary conditions is a main interest topic for EDF hydrologists. Thus, the scientific goal of this Ph.D. thesis work has been to evaluate the ability of the SCHADEX method to take into account future climate simulations for the estimation of future extreme floods. The recognized inabilities of climate models and down-scaling methods to simulate (extreme) rainfall distribution at the catchment-scale have been avoided, by developing and testing new methodological approaches. Moreover, the decomposition of the flood-producing factors proposed by the SCHADEX method has been used for considering different simulated climatic evolutions and for quantifying the relative impact of these factors on the extreme flood estimation. First, the SCHADEX method has been applied in present time over different climatic contexts (France, Austria, Canada and Norway), thanks to several colorations with academic and industrial partners. A sensitivity analysis allowed to quantify the extreme flood estimation sensitivity to rainfall hazard, catchment saturation hazard and rainfall-runoff transformation, independently. The results showed a large sensitivity of SCHADEX flood estimations to the rainfall hazard and to the rainfall-runoff transformation. Using the sensitivity analysis results, tests have been done in order to estimate the future evolution of 'key' variables previously identified. New climate model outputs (done within the CMIP5 project) have been analyzed and used for determining future frequency of rainfall events and future catchment saturation conditions. Considering these simulated evolutions within the SCHADEX method lead to a significant decrease of
Yang, T.; Lee, C.
2017-12-01
The biases in the Global Circulation Models (GCMs) are crucial for understanding future climate changes. Currently, most bias correction methodologies suffer from the assumption that model bias is stationary. This paper provides a non-stationary bias correction model, termed Residual-based Bagging Tree (RBT) model, to reduce simulation biases and to quantify the contributions of single models. Specifically, the proposed model estimates the residuals between individual models and observations, and takes the differences between observations and the ensemble mean into consideration during the model training process. A case study is conducted for 10 major river basins in Mainland China during different seasons. Results show that the proposed model is capable of providing accurate and stable predictions while including the non-stationarities into the modeling framework. Significant reductions in both bias and root mean squared error are achieved with the proposed RBT model, especially for the central and western parts of China. The proposed RBT model has consistently better performance in reducing biases when compared to the raw ensemble mean, the ensemble mean with simple additive bias correction, and the single best model for different seasons. Furthermore, the contribution of each single GCM in reducing the overall bias is quantified. The single model importance varies between 3.1% and 7.2%. For different future scenarios (RCP 2.6, RCP 4.5, and RCP 8.5), the results from RBT model suggest temperature increases of 1.44 ºC, 2.59 ºC, and 4.71 ºC by the end of the century, respectively, when compared to the average temperature during 1970 - 1999.
Woźniak, M.
2016-06-02
We study the features of a new mixed integration scheme dedicated to solving the non-stationary variational problems. The scheme is composed of the FEM approximation with respect to the space variable coupled with a 3-leveled time integration scheme with a linearized right-hand side operator. It was applied in solving the Cahn-Hilliard parabolic equation with a nonlinear, fourth-order elliptic part. The second order of the approximation along the time variable was proven. Moreover, the good scalability of the software based on this scheme was confirmed during simulations. We verify the proposed time integration scheme by monitoring the Ginzburg-Landau free energy. The numerical simulations are performed by using a parallel multi-frontal direct solver executed over STAMPEDE Linux cluster. Its scalability was compared to the results of the three direct solvers, including MUMPS, SuperLU and PaSTiX.
DEFF Research Database (Denmark)
Åström, Helena Lisa Alexandra; Friis Hansen, P.; Garrè, Luca
2014-01-01
Urban flooding introduces significant risk to society. Non-stationarity leads to increased uncertainty and this is challenging to include in actual decision-making. The primary objective of this study was to develop a risk assessment and decision support framework for pluvial urban flood risk under...... non-stationary conditions using an influence diagram (ID) which is a Bayesian network (BN) extended with decision and utility nodes. Non-stationarity is considered to be the influence of climate change where extreme precipitation patterns change over time. The overall risk is quantified in monetary...... terms expressed as expected annual damage. The network is dynamic in as much as it assesses risk at different points in time. The framework provides means for decision-makers to assess how different decisions on flood adaptation affect the risk now and in the future. The result from the ID was extended...
Mullan, Donal; Chen, Jie; Zhang, Xunchang John
2016-02-01
Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.
International Nuclear Information System (INIS)
Gil, E; Orini, M; Bailón, R; Laguna, P; Vergara, J M; Mainardi, L
2010-01-01
In this paper we assessed the possibility of using the pulse rate variability (PRV) extracted from the photoplethysmography signal as an alternative measurement of the HRV signal in non-stationary conditions. The study is based on analysis of the changes observed during a tilt table test in the heart rate modulation of 17 young subjects. First, the classical indices of HRV analysis were compared to the indices from PRV in intervals where stationarity was assumed. Second, the time-varying spectral properties of both signals were compared by time-frequency (TF) and TF coherence analysis. Third, the effect of replacing PRV with HRV in the assessment of the changes of the autonomic modulation of the heart rate was considered. Time-invariant HRV and PRV indices showed no statistically significant differences (p > 0.05) and high correlation (>0.97). Time-frequency analysis revealed that the TF spectra of both signals were highly correlated (0.99 ± 0.01); the difference between the instantaneous power, in the LF and HF bands, obtained from HRV and PRV was small (<10 −3 s −2 ) and their temporal patterns were highly correlated (0.98 ± 0.04 and 0.95 ± 0.06 in the LF and HF bands, respectively) and TF coherence in the LF and HF bands was high (0.97 ± 0.04 and 0.89 ± 0.08, respectively). Finally, the instantaneous power in the LF band was observed to significantly increase during head-up tilt by both HRV and PRV analysis. These results suggest that although some differences in the time-varying spectral indices extracted from HRV and PRV exist, mainly in the HF band associated with respiration, PRV could be used as a surrogate of HRV during non-stationary conditions, at least during the tilt table test
2018-03-01
to develop novel co-prime sampling and array design strategies that achieve high-resolution estimation of spectral power distributions and signal...by the array geometry and the frequency offset. We overcome this limitation by introducing a novel sparsity-based multi-target localization approach...estimation using a sparse uniform linear array with two CW signals of co-prime frequencies,” IEEE International Workshop on Computational Advances
Kolodyazhnaya, Lyubov Vladimirovna; Rzadkowski, Romuald; Gnesin, Vitaly Isaevich
2016-01-01
A problem related to the forecast of the aeroelastic behavior and aeroelastic instability of blades (in particular self-oscillations, flutter, and resonance vibrations) becomes of great importance for the development of high-loaded compressor and vent rows and the last turbine stages whose long and flexible blades can be exposed to such phenomena. The solution of this problem requires the development of new models for the nonstationary three-dimensional flow, the use of contemporary numeric m...
International Nuclear Information System (INIS)
Avezova, N.R.; Avezov, R.R.; Rashidov, Y.K. et al.
2014-01-01
The results of the model-based study of nonstationary thermal mode in premises with an insolation passive heating system with a three-layer translucent shield are presented. The article is aimed at determining daily variations in the air temperature of the heated premise on typical heating season days and analyzing the optimization of the thermal capacity of the short-term (daily) thermal battery of the heating system on this basis. (author)
DEFF Research Database (Denmark)
Köylüoglu, H. U.; Nielsen, Søren R. K.; Cakmak, A. S.
Geometrically non-linear multi-degree-of-freedom (MDOF) systems subject to random excitation are considered. New semi-analytical approximate forward difference equations for the lower order non-stationary statistical moments of the response are derived from the stochastic differential equations...... of motion, and, the accuracy of these equations is numerically investigated. For stationary excitations, the proposed method computes the stationary statistical moments of the response from the solution of non-linear algebraic equations....
International Nuclear Information System (INIS)
Bol, G H; Lagendijk, J J W; Raaymakers, B W
2015-01-01
With the development of the 1.5 T MRI linear accelerator and the clinical introduction of the 0.35 T ViewRay™ system, delivering intensity-modulated radiotherapy (IMRT) in a transverse magnetic field becomes increasingly important. When delivering dose in the presence of a transverse magnetic field, one of the most prominent phenomena occurs around air cavities: the electron return effect (ERE). For stationary, spherical air cavities which are centrally located in the phantom, the ERE can be compensated by using opposing beams configurations in combination with IMRT. In this paper we investigate the effects of non-stationary spherical air cavities, centrally located within the target in a phantom containing no organs at risk, on IMRT dose delivery in 0.35 T and 1.5 T transverse magnetic fields by using Monte Carlo simulations. We show that IMRT can be used for compensating ERE around those air cavities, except for intrafraction appearing or disappearing air cavities. For these cases, gating or plan re-optimization should be used. We also analyzed the option of using IMRT plans optimized at 0 T to be delivered in the presence of 0.35 T and 1.5 T magnetic field. When delivering dose at 0.35 T, IMRT plans optimized at 0 T and 0.35 T perform equally well regarding ERE compensation. Within a 1.5 T environment, the 1.5 T optimized plans perform slightly better for the static and random intra- and interfraction air cavity movement cases than the 0 T optimized plans. For non-stationary spherical air cavities with a baseline shift (intra- and interfraction) the 0 T optimized plans perform better. These observations show the intrinsic ERE compensation by equidistant and opposing beam configurations for spherical air cavities within the target area. IMRT gives some additional compensation, but only in case of correct positioning of the air cavity according to the IMRT compensation. For intrafraction appearing or disappearing air cavities this correct
Quantifying advective and nonstationary effects on eddy fluxes in the AmeriFlux network
Energy Technology Data Exchange (ETDEWEB)
Fitzjarrald, David R
2012-12-19
Our goal was to study the flows within and above of a forested area and assess the degree to which horizontal subcanopy motions transport significant amounts of CO2. This process can explain why ecosystem respiration appears to be underestimated on calm nights. It is essential to understand the physical and biological mechanisms that determine relevant processes that occur on these suspect nights.
International Nuclear Information System (INIS)
Bocek, M.; Armas, I.
1982-01-01
It was the aim of the present investigation to examine how the recovery rate in creep is influenced by a non-stationary stress. For purposes of phenomenological analysis it is postulated that, irrespective of whether the applied stress is stationary or not, for large strains the mean internal stress sigmasub(i) approaches a stationary value sigmasub(i,s). The stationary recovery rate Rsub(s) for constant load creep turns out be governed by the applied stress indicating that the recovery mechanism is dynamic in nature. For sigma-ramp loading, Rsub(s) is dependent on the stress rate sigma. In tensional stress cycling, Rsub(s) is governed by the maximum stress sigmasub(M) and is also dependent on the ratio of sigmasub(M) to the minimum stress sigma 0 . TEM examination of Zircaloy-4 specimens crept at 800 0 C at constant and cycling load respectively could not reveal any differences in the deformation substructure for the two loading types. Subgrain formation did not appear, individual dislocations were observed only rarely. However, typical networks were formed as well as pileups which perhaps are responsible for the back stress in high temperature plasticity (HTP). (orig.)
Korelin, Ivan A.; Porshnev, Sergey V.
2018-05-01
A model of the non-stationary queuing system (NQS) is described. The input of this model receives a flow of requests with input rate λ = λdet (t) + λrnd (t), where λdet (t) is a deterministic function depending on time; λrnd (t) is a random function. The parameters of functions λdet (t), λrnd (t) were identified on the basis of statistical information on visitor flows collected from various Russian football stadiums. The statistical modeling of NQS is carried out and the average statistical dependences are obtained: the length of the queue of requests waiting for service, the average wait time for the service, the number of visitors entered to the stadium on the time. It is shown that these dependencies can be characterized by the following parameters: the number of visitors who entered at the time of the match; time required to service all incoming visitors; the maximum value; the argument value when the studied dependence reaches its maximum value. The dependences of these parameters on the energy ratio of the deterministic and random component of the input rate are investigated.
Directory of Open Access Journals (Sweden)
Yubo Wang
2017-06-01
Full Text Available It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC. In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976 ratio and outperforms existing methods such as short-time Fourier transfrom (STFT, continuous Wavelet transform (CWT and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
Wang, Yubo; Veluvolu, Kalyana C
2017-06-14
It is often difficult to analyze biological signals because of their nonlinear and non-stationary characteristics. This necessitates the usage of time-frequency decomposition methods for analyzing the subtle changes in these signals that are often connected to an underlying phenomena. This paper presents a new approach to analyze the time-varying characteristics of such signals by employing a simple truncated Fourier series model, namely the band-limited multiple Fourier linear combiner (BMFLC). In contrast to the earlier designs, we first identified the sparsity imposed on the signal model in order to reformulate the model to a sparse linear regression model. The coefficients of the proposed model are then estimated by a convex optimization algorithm. The performance of the proposed method was analyzed with benchmark test signals. An energy ratio metric is employed to quantify the spectral performance and results show that the proposed method Sparse-BMFLC has high mean energy (0.9976) ratio and outperforms existing methods such as short-time Fourier transfrom (STFT), continuous Wavelet transform (CWT) and BMFLC Kalman Smoother. Furthermore, the proposed method provides an overall 6.22% in reconstruction error.
International Nuclear Information System (INIS)
Liu, Jie
2015-01-01
This Ph. D. work is motivated by the possibility of monitoring the conditions of components of energy systems for their extended and safe use, under proper practice of operation and adequate policies of maintenance. The aim is to develop a Support Vector Regression (SVR)-based framework for predicting time series data under stationary/nonstationary environmental and operational conditions. Single SVR and SVR-based ensemble approaches are developed to tackle the prediction problem based on both small and large datasets. Strategies are proposed for adaptively updating the single SVR and SVR-based ensemble models in the existence of pattern drifts. Comparisons with other online learning approaches for kernel-based modelling are provided with reference to time series data from a critical component in Nuclear Power Plants (NPPs) provided by Electricite de France (EDF). The results show that the proposed approaches achieve comparable prediction results, considering the Mean Squared Error (MSE) and Mean Relative Error (MRE), in much less computation time. Furthermore, by analyzing the geometrical meaning of the Feature Vector Selection (FVS) method proposed in the literature, a novel geometrically interpretable kernel method, named Reduced Rank Kernel Ridge Regression-II (RRKRR-II), is proposed to describe the linear relations between a predicted value and the predicted values of the Feature Vectors (FVs) selected by FVS. Comparisons with several kernel methods on a number of public datasets prove the good prediction accuracy and the easy-of-tuning of the hyper-parameters of RRKRR-II. (author)
Energy Technology Data Exchange (ETDEWEB)
Azadeh, A; Seraj, O [Department of Industrial Engineering and Research Institute of Energy Management and Planning, Center of Excellence for Intelligent-Based Experimental Mechanics, College of Engineering, University of Tehran, P.O. Box 11365-4563 (Iran); Saberi, M [Department of Industrial Engineering, University of Tafresh (Iran); Institute for Digital Ecosystems and Business Intelligence, Curtin University of Technology, Perth (Australia)
2010-06-15
This study presents an integrated fuzzy regression and time series framework to estimate and predict electricity demand for seasonal and monthly changes in electricity consumption especially in developing countries such as China and Iran with non-stationary data. Furthermore, it is difficult to model uncertain behavior of energy consumption with only conventional fuzzy regression (FR) or time series and the integrated algorithm could be an ideal substitute for such cases. At First, preferred Time series model is selected from linear or nonlinear models. For this, after selecting preferred Auto Regression Moving Average (ARMA) model, Mcleod-Li test is applied to determine nonlinearity condition. When, nonlinearity condition is satisfied, the preferred nonlinear model is selected and defined as preferred time series model. At last, the preferred model from fuzzy regression and time series model is selected by the Granger-Newbold. Also, the impact of data preprocessing on the fuzzy regression performance is considered. Monthly electricity consumption of Iran from March 1994 to January 2005 is considered as the case of this study. The superiority of the proposed algorithm is shown by comparing its results with other intelligent tools such as Genetic Algorithm (GA) and Artificial Neural Network (ANN). (author)
Melkonian, D; Korner, A; Meares, R; Bahramali, H
2012-10-01
A novel method of the time-frequency analysis of non-stationary heart rate variability (HRV) is developed which introduces the fragmentary spectrum as a measure that brings together the frequency content, timing and duration of HRV segments. The fragmentary spectrum is calculated by the similar basis function algorithm. This numerical tool of the time to frequency and frequency to time Fourier transformations accepts both uniform and non-uniform sampling intervals, and is applicable to signal segments of arbitrary length. Once the fragmentary spectrum is calculated, the inverse transform recovers the original signal and reveals accuracy of spectral estimates. Numerical experiments show that discontinuities at the boundaries of the succession of inter-beat intervals can cause unacceptable distortions of the spectral estimates. We have developed a measure that we call the "RR deltagram" as a form of the HRV data that minimises spectral errors. The analysis of the experimental HRV data from real-life and controlled breathing conditions suggests transient oscillatory components as functionally meaningful elements of highly complex and irregular patterns of HRV. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Yu, Zhi-wu; Mao, Jian-feng; Guo, Feng-qi; Guo, Wei
2016-03-01
Rail irregularity is one of the main sources causing train-bridge random vibration. A new random vibration theory for the coupled train-bridge systems is proposed in this paper. First, number theory method (NTM) with 2N-dimensional vectors for the stochastic harmonic function (SHF) of rail irregularity power spectrum density was adopted to determine the representative points of spatial frequencies and phases to generate the random rail irregularity samples, and the non-stationary rail irregularity samples were modulated with the slowly varying function. Second, the probability density evolution method (PDEM) was employed to calculate the random dynamic vibration of the three-dimensional (3D) train-bridge system by a program compiled on the MATLAB® software platform. Eventually, the Newmark-β integration method and double edge difference method of total variation diminishing (TVD) format were adopted to obtain the mean value curve, the standard deviation curve and the time-history probability density information of responses. A case study was presented in which the ICE-3 train travels on a three-span simply-supported high-speed railway bridge with excitation of random rail irregularity. The results showed that compared to the Monte Carlo simulation, the PDEM has higher computational efficiency for the same accuracy, i.e., an improvement by 1-2 orders of magnitude. Additionally, the influences of rail irregularity and train speed on the random vibration of the coupled train-bridge system were discussed.