Статті в журналах з теми "Piecewise stationarity"

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1

Prasolov, Aleksander V., Nikita G. Ivanov, and Nikolay V. Smirnov. "Algorithm of variance estimation in weighted least squares method." Vestnik of Saint Petersburg University. Applied Mathematics. Computer Science. Control Processes 19, no. 4 (2023): 484–96. http://dx.doi.org/10.21638/11701/spbu10.2023.405.

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The representation of a time series model as a piecewise-stationary process is provided, wherein it is regarded as a collection of successive stationary intervals. An algorithm has been developed for identifying the domain containing the trend within this model. It is recognized that applying the least squares method directly for trend determination is not commonly employed in statistical analysis and econometric software packages. Typically, the weighted least squares method is utilized to ideally eliminate non-stationarity. The authors presents an algorithm for estimating the weight coefficients for this method through piecewise-stationary modeling. The algorithm has been tested on time series of various natures.
2

Fell, Jürgen, Alexander Kaplan, Boris Darkhovsky, and Joachim Röschke. "EEG analysis with nonlinear deterministic and stochastic methods: a combined strategy." Acta Neurobiologiae Experimentalis 60, no. 1 (March 31, 2000): 87–108. http://dx.doi.org/10.55782/ane-2000-1328.

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We describe nonlinear deterministic versus stochastic methodology, their applications to EEG research and the neurophysiological background underlying both approaches. Nonlinear methods are based on the concept of attractors in phase space. This concept on the one hand incorporates the idea of an autonomous (stationary) system, on the other hand implicates the investigation of a long time evolution. It is an unresolved problem in nonlinear EEG research that nonlinear methods per se give no feedback about the stationarity aspect. Hence, we introduce a combined strategy utilizing both stochastic and nonlinear deterministic methods. We propose, in a first step to segment the EEG time series into piecewise quasi-stationary epochs by means of nonparametric change point analysis. Subsequently, nonlinear measures can be estimated with higher confidence for the segmented epochs fullfilling the stationarity condition.
3

Seleznjev, Oleg. "Large deviations in the piecewise linear approximation of Gaussian processes with stationary increments." Advances in Applied Probability 28, no. 2 (June 1996): 481–99. http://dx.doi.org/10.2307/1428068.

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We consider the piecewise linear interpolation of Gaussian processes with continuous sample paths and stationary increments. The interrelation between the smoothness of the incremental variance function, d(t – s) = E[(X(t) – X(s))2], and the interpolation errors in mean square and uniform metrics is studied. The method of investigation can also be applied to the analysis of different methods of interpolation. It is based on some limit results for large deviations of a sequence of Gaussian non-stationary processes and related point processes. Non-stationarity in our case means mainly the local stationary condition for the sequence of correlation functions rn(t,s), n = 1, 2, ···, which has to hold uniformly in n. Finally, we discuss some examples and an application to the calculation of the distribution function of the maximum of a continuous Gaussian process with a given precision.
4

Seleznjev, Oleg. "Large deviations in the piecewise linear approximation of Gaussian processes with stationary increments." Advances in Applied Probability 28, no. 02 (June 1996): 481–99. http://dx.doi.org/10.1017/s0001867800048588.

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We consider the piecewise linear interpolation of Gaussian processes with continuous sample paths and stationary increments. The interrelation between the smoothness of the incremental variance function, d(t – s) = E[(X(t) – X(s))2], and the interpolation errors in mean square and uniform metrics is studied. The method of investigation can also be applied to the analysis of different methods of interpolation. It is based on some limit results for large deviations of a sequence of Gaussian non-stationary processes and related point processes. Non-stationarity in our case means mainly the local stationary condition for the sequence of correlation functions rn(t, s), n = 1, 2, ···, which has to hold uniformly in n. Finally, we discuss some examples and an application to the calculation of the distribution function of the maximum of a continuous Gaussian process with a given precision.
5

PODIO-GUIDUGLI, PAOLO, and GIORGIO VERGARA CAFFARELLI. "EQUILIBRIUM PHASES AND LAYERED PHASE MIXTURES IN ELASTICITY." Mathematical Models and Methods in Applied Sciences 02, no. 02 (June 1992): 143–66. http://dx.doi.org/10.1142/s0218202592000107.

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In this paper an equilibrium phase is a restriction of a piecewise-affine deformation of a body to a (maximal, connected) subbody whose deformation is affine; a layered phase mixture is a continuous deformation that admits at least two distinct phases, separated by a plane interface. We study equilibrium phases and layered phase mixtures in the context of finite elasticity, in the presence of three different boundary conditions of traction: uniform pressure, and two other of null Lagrangians. In Part I we reduce to a unique format the stationarity condition for the existence of equilibrium phases — of the conformal, transversely symmetric and asymmetric types — in elastic materials of arbitrary mechanical response; and we determine reasonable assumptions under which the stationary points of a (generalized) free energy are indeed equilibrium phases. In Part II we restrict attention to isotropic material, and give explicit stationarity and compatibility conditions for the existence of mixtures of two layered, transversely symmetric phases.
6

Moltchanov, D. "Modeling local stationary behavior of Internet traffic." Journal of Communications Software and Systems 4, no. 1 (March 20, 2008): 41. http://dx.doi.org/10.24138/jcomss.v4i1.236.

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Non-stationary behavior of aggregated IP traffic patterns was demonstrated in a number of studies. However, noneof those did either consider practical aspects of this phenomenon or propose suitable model to capture it. Searching for model for IP traffic aggregates we introduce the concept of local stationarity and demonstrate that it allows to model traffic patterns measured in high-speed operational networks. The proposed model is on-line in nature and suitable for real-time estimation of the traffic state in terms of piecewise covariance stationary stochasticprocess. As a basic tool of the model we use change-pointstatistical test allowing us to dynamically and automaticallydetermine whether statistical characteristics of the traffic pattern changes and, if so, estimate new parameters of the traffic pattern. We provide numerical examples and discuss applications of the proposed model that include but not limited to dynamic resource reservation, routing with guaranteed bandwidth, etc.
7

Rosenthal, Jeffrey S. "Random walks on discrete and continuous circles." Journal of Applied Probability 30, no. 4 (December 1993): 780–89. http://dx.doi.org/10.2307/3214512.

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We consider a large class of random walks on the discrete circle Z/(n), defined in terms of a piecewise Lipschitz function, and motivated by the ‘generation gap' process of Diaconis. For such walks, we show that the time until convergence to stationarity is bounded independently of n. Our techniques involve Fourier analysis and a comparison of the random walks on Z/(n) with a random walk on the continuous circle S1.
8

Rosenthal, Jeffrey S. "Random walks on discrete and continuous circles." Journal of Applied Probability 30, no. 04 (December 1993): 780–89. http://dx.doi.org/10.1017/s0021900200044569.

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We consider a large class of random walks on the discrete circle Z/(n), defined in terms of a piecewise Lipschitz function, and motivated by the ‘generation gap' process of Diaconis. For such walks, we show that the time until convergence to stationarity is bounded independently of n. Our techniques involve Fourier analysis and a comparison of the random walks on Z/(n) with a random walk on the continuous circle S 1.
9

van der Baan, Mirko, and Sergey Fomel. "Nonstationary phase estimation using regularized local kurtosis maximization." GEOPHYSICS 74, no. 6 (November 2009): A75—A80. http://dx.doi.org/10.1190/1.3213533.

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Phase mismatches sometimes occur between final processed seismic sections and zero-phase synthetics based on well logs — despite best efforts for controlled-phase acquisition and processing. Statistical estimation of the phase of a seismic wavelet is feasible using kurtosis maximization by constant-phase rotation, even if the phase is nonstationary. We cast the phase-estimation problem into an optimization framework to improve the stability of an earlier method based on a piecewise-stationarity assumption. After estimation, we achieve space-and-time-varying zero-phasing by phase rotation.
10

NAKATSUJI, Takashi, and Terutoshi KAKU. "IMPROVEMENT OF PREDICTION SCHEME OF TRAFFIC FLOW ON URBAN STREETS BASED ON PIECEWISE STATIONARITY." INFRASTRUCTURE PLANNING REVIEW 4 (1986): 101–8. http://dx.doi.org/10.2208/journalip.4.101.

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11

Dong, Li, Jiantao Zhou, and Yuan Yan Tang. "Noise Level Estimation for Natural Images Based on Scale-Invariant Kurtosis and Piecewise Stationarity." IEEE Transactions on Image Processing 26, no. 2 (February 2017): 1017–30. http://dx.doi.org/10.1109/tip.2016.2639447.

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12

Echavarria-Heras, Héctor A., Cecilia Leal-Ramírez, Guillermo Gómez, and Elia Montiel-Arzate. "Principle of Limiting Factors-Driven Piecewise Population Growth Model I: Qualitative Exploration and Study Cases on Continuous-Time Dynamics." Complexity 2021 (December 27, 2021): 1–24. http://dx.doi.org/10.1155/2021/5623783.

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We examine the comportment of the global trajectory of a piecewisely conceived single species population growth model. Formulation relies on what we develop as the principle of limiting factors for population growth, adapted from the law of the minimum of Liebig and the law of the tolerance of Shelford. The ensuing paradigm sets natality and mortality rates to express through extreme values of population growth determining factor. Dynamics through time occur over different growth phases. Transition points are interpreted as thresholds of viability, starvation, and intraspecific competition. In this delivery, we focus on the qualitative study of the global trajectory expressed on continuous time and on exploring the feasibility of analytical results against data on populations growing under experimental or natural conditions. All study cases sustained fittings of high reproducibility both at empirical and interpretative slants. Possible phase configurations include regimes with multiple stable equilibria, sigmoidal growth, extinction, or stationarity. Here, we also outline that the associating discrete-time piecewise model composes the logistic map applied over a particular region of the phase configuration. Preliminary exploratory analysis suggests that the logistic map’s chaos onset could surpass once the orbit enters a contiguous phase region.
13

Luo, Yuwei, Varun Gupta, and Mladen Kolar. "Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems." ACM SIGMETRICS Performance Evaluation Review 50, no. 1 (June 20, 2022): 75–76. http://dx.doi.org/10.1145/3547353.3522649.

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We consider the problem of controlling a Linear Quadratic Regulator (LQR) system over a finite horizon T with fixed and known cost matrices Q,R, but unknown and non-stationary dynamics At, Bt. The sequence of dynamics matrices can be arbitrary, but with a total variation, VT, assumed to be o(T) and unknown to the controller. Under the assumption that a sequence of stabilizing, but potentially sub-optimal controllers is available for all t, we present an algorithm that achieves the optimal dynamic regret of Õ(VT2/5 T3/5). With piecewise constant dynamics, our algorithm achieves the optimal regret of Õ(√ST) where S is the number of switches. The crux of our algorithm is an adaptive non-stationarity detection strategy, which builds on an approach recently developed for contextual Multi-armed Bandit problems. We also argue that non-adaptive forgetting (e.g., restarting or using sliding window learning with a static window size) may not be regret optimal for the LQR problem, even when the window size is optimally tuned with the knowledge of VT. The main technical challenge in the analysis of our algorithm is to prove that the ordinary least squares (OLS) estimator has a small bias when the parameter to be estimated is non-stationary. Our analysis also highlights that the key motif driving the regret is that the LQR problem is in spirit a bandit problem with linear feedback and locally quadratic cost. This motif is more universal than the LQR problem itself, and therefore we believe our results should find wider application.
14

Luo, Yuwei, Varun Gupta, and Mladen Kolar. "Dynamic Regret Minimization for Control of Non-stationary Linear Dynamical Systems." Proceedings of the ACM on Measurement and Analysis of Computing Systems 6, no. 1 (February 24, 2022): 1–72. http://dx.doi.org/10.1145/3508029.

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We consider the problem of controlling a Linear Quadratic Regulator (LQR) system over a finite horizon T with fixed and known cost matrices Q,R, but unknown and non-stationary dynamics A_t, B_t. The sequence of dynamics matrices can be arbitrary, but with a total variation, V_T, assumed to be o(T) and unknown to the controller. Under the assumption that a sequence of stabilizing, but potentially sub-optimal controllers is available for all t, we present an algorithm that achieves the optimal dynamic regret of O(V_T^2/5 T^3/5 ). With piecewise constant dynamics, our algorithm achieves the optimal regret of O(sqrtST ) where S is the number of switches. The crux of our algorithm is an adaptive non-stationarity detection strategy, which builds on an approach recently developed for contextual Multi-armed Bandit problems. We also argue that non-adaptive forgetting (e.g., restarting or using sliding window learning with a static window size) may not be regret optimal for the LQR problem, even when the window size is optimally tuned with the knowledge of $V_T$. The main technical challenge in the analysis of our algorithm is to prove that the ordinary least squares (OLS) estimator has a small bias when the parameter to be estimated is non-stationary. Our analysis also highlights that the key motif driving the regret is that the LQR problem is in spirit a bandit problem with linear feedback and locally quadratic cost. This motif is more universal than the LQR problem itself, and therefore we believe our results should find wider application.
15

Kumar, Jitendra, Varun Varun, Dhirendra Kumar, and Anoop Chaturvedi. "Bayesian Unit Root Test for AR(1) Model with Trend Approximated." Statistics, Optimization & Information Computing 8, no. 2 (May 27, 2020): 425–61. http://dx.doi.org/10.19139/soic-2310-5070-786.

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The objective of present study is to develop a time series model for handling the non-linear trend process using a spline function. Spline function is a piecewise polynomial segment concerning the time component. The main advantage of spline function is the approximation, non linear time trend, but linear time trend between the consecutive join points. A unit root hypothesis is projected to test the non stationarity due to presence of unit root in the proposed model. In the autoregressive model with linear trend, the time trend vanishes under the unit root case. However, when non-linear trend is present and approximated by the linear spline function, through the trend component is absent under the unit root case, but the intercept term makes a shift with r knots. For decision making under the Bayesian perspective, the posterior odds ratio is used for hypothesis testing problems. We have derived the posterior probability for the assumed hypotheses under appropriate prior information. A simulation study and an empirical application are presented to examine the performance of theoretical outcomes.
16

Mamtiyev, Kamil, Tarana Aliyeva, and Ulviyye Rzayeva. "Solution of one optimum control problem regarding the depletion of gas reservoir." Eastern-European Journal of Enterprise Technologies 1, no. 4 (115) (February 25, 2022): 6–13. http://dx.doi.org/10.15587/1729-4061.2022.252743.

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Using the methods of the optimal control theory, the problem of determining the optimal technological mode of gas deposits’ exploitation under the condition of their depletion by a given point in time is solved. This task is of particular interest for the exploitation of offshore fields, the activity of which is limited by the service life of the field equipment. The considered problem is also of certain mathematical interest as an objective of optimal control of nonlinear systems with distributed parameters. The usefulness and importance of solving such problems are determined by the richness of the class of major tasks that have a practical result. As an optimality criterion, a quadratic functional characterizing the conditions of reservoir depletion is considered. By introducing an auxiliary boundary value problem, and taking into account the stationarity conditions for the Lagrange functions at the optimal point, a formula for the gradient of the minimized functional is obtained. To obtain a solution to this specific optimization problem, which control function is sought in the class of a piecewise continuous and bounded function with discontinuities of the first kind, the Pontryagin’s maximum principle is subjected. The calculation of the gradient of the functional for the original and adjoint problems with partial differential equations is carried out by the method of straight lines. The numerical solution of the problem was carried out by two methods – the method of gradient projection with a special choice of step and the method of successive approximations. Despite the incorrectness of optimal control problems with a quadratic functional, the gradient projection method did not show a tendency to «dispersion» and gave a convergent sequence of controls.
17

LEE, AN-CHEN, and JIING-SHYANG CHOU. "Segmentation of piecewise stationary signals." International Journal of Systems Science 20, no. 10 (October 1989): 1827–42. http://dx.doi.org/10.1080/00207728908910268.

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18

Zhou, Huozhi, Lingda Wang, Lav Varshney, and Ee-Peng Lim. "A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 04 (April 3, 2020): 6933–40. http://dx.doi.org/10.1609/aaai.v34i04.6176.

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We investigate the piecewise-stationary combinatorial semi-bandit problem. Compared to the original combinatorial semi-bandit problem, our setting assumes the reward distributions of base arms may change in a piecewise-stationary manner at unknown time steps. We propose an algorithm, GLR-CUCB, which incorporates an efficient combinatorial semi-bandit algorithm, CUCB, with an almost parameter-free change-point detector, the Generalized Likelihood Ratio Test (GLRT). Our analysis shows that the regret of GLR-CUCB is upper bounded by O(√NKT log T), where N is the number of piecewise-stationary segments, K is the number of base arms, and T is the number of time steps. As a complement, we also derive a nearly matching regret lower bound on the order of Ω(√NKT), for both piecewise-stationary multi-armed bandits and combinatorial semi-bandits, using information-theoretic techniques and judiciously constructed piecewise-stationary bandit instances. Our lower bound is tighter than the best available regret lower bound, which is Ω(√T). Numerical experiments on both synthetic and real-world datasets demonstrate the superiority of GLR-CUCB compared to other state-of-the-art algorithms.
19

Costa, O. L. V. "Stationary distributions for piecewise-deterministic Markov processes." Journal of Applied Probability 27, no. 1 (March 1990): 60–73. http://dx.doi.org/10.2307/3214595.

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In this paper we show that the problem of existence and uniqueness of stationary distributions for piecewise-deterministic Markov processes (PDPs) is equivalent to the same problem for the associated Markov chain, so long as some mild conditions on the parameters of the PDP are satisfied. Our main result is the construction of an invertible mapping from the set of stationary distributions for the PDP to the set of stationary distributions for the Markov chain. Some sufficient conditions for existence are presented and an application to capacity expansion is given.
20

Costa, O. L. V. "Stationary distributions for piecewise-deterministic Markov processes." Journal of Applied Probability 27, no. 01 (March 1990): 60–73. http://dx.doi.org/10.1017/s0021900200038420.

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In this paper we show that the problem of existence and uniqueness of stationary distributions for piecewise-deterministic Markov processes (PDPs) is equivalent to the same problem for the associated Markov chain, so long as some mild conditions on the parameters of the PDP are satisfied. Our main result is the construction of an invertible mapping from the set of stationary distributions for the PDP to the set of stationary distributions for the Markov chain. Some sufficient conditions for existence are presented and an application to capacity expansion is given.
21

Xu, Pengfei, and Yinjie Jia. "SNR improvement based on piecewise linear interpolation." Journal of Electrical Engineering 72, no. 5 (September 1, 2021): 348–51. http://dx.doi.org/10.2478/jee-2021-0049.

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Abstract Interpolation improves the resolution of the curve. Based on the stationary characteristics of the signal and the non-stationary characteristics of the noise, the theoretical proof indicates that the piecewise linear interpolation can improve the signal-to-noise ratio, which is further confirmed by simulation results.
22

Morgan, Matthew R., Gregg E. Trahey, and William F. Walker. "Speckle coherence of piecewise-stationary stochastic targets." Journal of the Acoustical Society of America 146, no. 3 (September 2019): 1721–31. http://dx.doi.org/10.1121/1.5126686.

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23

Begovatov, E. A., and N. P. Evlampiev. "Correlation function of a piecewise-stationary process." Journal of Soviet Mathematics 45, no. 2 (April 1989): 1084–88. http://dx.doi.org/10.1007/bf01095706.

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24

BOFFI, D. "STABILITY OF HIGHER ORDER TRIANGULAR HOOD-TAYLOR METHODS FOR THE STATIONARY STOKES EQUATIONS." Mathematical Models and Methods in Applied Sciences 04, no. 02 (April 1994): 223–35. http://dx.doi.org/10.1142/s0218202594000133.

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We prove the stability for the approximation of the stationary Stokes equations by means of piecewise continuous velocities of degree k+1 and piecewise continuous pressures of degree k for k≥1. The necessary and sufficient condition required on the triangulation is that it contains at least three triangles. The theorem is compared with previous results.
25

Koldovský, Zbyněk, Jiří Málek, Petr Tichavský, Yannick Deville, and Shahram Hosseini. "Blind separation of piecewise stationary non-Gaussian sources." Signal Processing 89, no. 12 (December 2009): 2570–84. http://dx.doi.org/10.1016/j.sigpro.2009.04.021.

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26

Fujii, Takayuki. "Nonparametric Estimation for a Class of Piecewise-Deterministic Markov Processes." Journal of Applied Probability 50, no. 4 (December 2013): 931–42. http://dx.doi.org/10.1239/jap/1389370091.

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In this paper we study nonparametric estimation problems for a class of piecewise-deterministic Markov processes (PDMPs). Borovkov and Last (2008) proved a version of Rice's formula for PDMPs, which explains the relation between the stationary density and the level crossing intensity. From a statistical point of view, their result suggests a methodology for estimating the stationary density from observations of a sample path of PDMPs. First, we introduce the local time related to the level crossings and construct the local-time estimator for the stationary density, which is unbiased and uniformly consistent. Secondly, we investigate other estimation problems for the jump intensity and the conditional jump size distribution.
27

Fujii, Takayuki. "Nonparametric Estimation for a Class of Piecewise-Deterministic Markov Processes." Journal of Applied Probability 50, no. 04 (December 2013): 931–42. http://dx.doi.org/10.1017/s0021900200013711.

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In this paper we study nonparametric estimation problems for a class of piecewise-deterministic Markov processes (PDMPs). Borovkov and Last (2008) proved a version of Rice's formula for PDMPs, which explains the relation between the stationary density and the level crossing intensity. From a statistical point of view, their result suggests a methodology for estimating the stationary density from observations of a sample path of PDMPs. First, we introduce the local time related to the level crossings and construct the local-time estimator for the stationary density, which is unbiased and uniformly consistent. Secondly, we investigate other estimation problems for the jump intensity and the conditional jump size distribution.
28

Fan, Zhi Ping, Tian Sheng Hong, Zhi Zhuan Liu, and Zheng Zhe Jing. "Improve the Envelope of EMD with Piecewise Linear Fractal Interpolation." Key Engineering Materials 439-440 (June 2010): 390–95. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.390.

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Empirical mode decomposition (EMD) has recently been pioneered by Huang et al. for adaptively representing non-stationary signals as sums of zero-mean amplitude modulation frequency modulation components. The traditional EMD algorithm adopts the cubic spline interpolation as an effective tool processing non-stationary signal, but it cannot effectively extract the characteristic frequencies from a highly non-stationary signal, and the overshoots and the undershoots may become a common phenomenon during the decomposition process. In order to solve the problem, we presents the piecewise linear fractal interpolation as the spline interpolating. Finally, we will use the simulation signal to verify the effectiveness of the improved EMD.
29

Sireteanu, Tudor, Ana-Maria Mitu, Ovidiu Solomon, and Marius Giuclea. "Approximation of the Statistical Characteristics of Piecewise Linear Systems with Asymmetric Damping and Stiffness under Stationary Random Excitation." Mathematics 10, no. 22 (November 15, 2022): 4275. http://dx.doi.org/10.3390/math10224275.

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In this paper, the dynamic response of piecewise linear systems with asymmetric damping and stiffness for random excitation is studied. In order to approximate the statistical characteristics for each significant output of piecewise linear system, a method based on transmissibility factors is applied. A stochastic linear system with the same transmissibility factor is attached, and the statistical parameters of the studied output corresponding to random excitation having rational spectral densities are determined by solving the associated Lyapunov equation. Using the attached linear systems for root mean square and for standard deviation of displacement, the shift of the sprung mass average position in a dynamic regime, due to damping or stiffness asymmetry, can be predicted with a good accuracy for stationary random input. The obtained results are compared with those determined by the Gaussian equivalent linearization method and by the numerical integration of asymmetric piecewise linear system equations. It is shown that the piecewise linear systems with asymmetrical damping and stiffness characteristics can provide a better vibration isolation (lower force transmissibility) than the linear system.
30

CHENG, Hao, Guo-qing LIU, and Xiao-gang CHENG. "Approximation model of piecewise stationary stochastic process autocorrelation function." Journal of Computer Applications 32, no. 2 (March 15, 2013): 589–91. http://dx.doi.org/10.3724/sp.j.1087.2012.00589.

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31

Borovkov, K., and G. Last. "On Rice's Formula for Stationary Multivariate Piecewise Smooth Processes." Journal of Applied Probability 49, no. 2 (June 2012): 351–63. http://dx.doi.org/10.1239/jap/1339878791.

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Let X = {Xt: t ≥ 0} be a stationary piecewise continuous Rd-valued process that moves between jumps along the integral curves of a given continuous vector field, and let S ⊂ Rd be a smooth surface. The aim of this paper is to derive a multivariate version of Rice's formula, relating the intensity of the point process of (localized) continuous crossings of S by X to the distribution of X0. Our result is illustrated by examples relating to queueing networks and stress release network models.
32

Borovkov, K., and G. Last. "On Rice's Formula for Stationary Multivariate Piecewise Smooth Processes." Journal of Applied Probability 49, no. 02 (June 2012): 351–63. http://dx.doi.org/10.1017/s002190020000913x.

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LetX= {Xt:t≥ 0} be a stationary piecewise continuousRd-valued process that moves between jumps along the integral curves of a given continuous vector field, and letS⊂Rdbe a smooth surface. The aim of this paper is to derive a multivariate version of Rice's formula, relating the intensity of the point process of (localized) continuous crossings ofSbyXto the distribution ofX0. Our result is illustrated by examples relating to queueing networks and stress release network models.
33

吴, 楠. "Multiple Change-Points Detection of Piecewise Stationary Time Series." Pure Mathematics 08, no. 02 (2018): 136–48. http://dx.doi.org/10.12677/pm.2018.82018.

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34

ALIEV, A. B., A. N. HUSEYNOVA, and G. A. ALIYEV. "A MIXED PROBLEM FOR A ONE-DIMENSIONAL VISCOELASTICITY EQUATION WITH NON-STATIONARY CONJUGATION CONDITIONS." Baku Mathematical Journal 1, no. 1 (March 31, 2022): 63–77. http://dx.doi.org/10.32010/j.bmj.2022.07.

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The problem of a longitudinal impact on a piecewise homogeneous semiinfinite rod consisting of viscoelastic parts is studied. Introducing non-stationary dynamic regularization under conjugation conditions, we prove the well-posedness of the problem under consideration
35

Zhang, Lu, Wenqi Wu, and Maosong Wang. "Rapid SINS Two-Position Ground Alignment Scheme Based on Piecewise Combined Kalman Filter and Azimuth Constraint Information." Sensors 19, no. 5 (March 5, 2019): 1125. http://dx.doi.org/10.3390/s19051125.

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The accuracy and rate of convergence are two important performance factors for initial ground alignment of a strapdown inertial navigation system (SINS). For navigation-grade SINS, gyro biases and accelerometer offsets can be modeled as constant values during the alignment period, and they can be calibrated through two-position ground alignment schemes. In many situations for SINS ground alignment, the azimuth of the vehicle remains nearly constant. This quasi-stationary alignment information can be used as an augmented measurement. In this paper, a piecewise combined Kalman filter utilizing relative azimuth constraint (RATP) is proposed to improve the alignment precision and to reduce the time consumption for error convergence. It is presented that a piecewise time-invariant linear system can be combined into a whole extended time-invariant linear system so that a piecewise combined Kalman filter can be designed for state estimation. A two-position ground alignment algorithm for SINS is designed based on the proposed piecewise combined Kalman filter. Numerical simulations and experimental results show its superiority to the conventional algorithms in terms of accuracy and the rate of convergence.
36

Freimanis, Juris. "Polarized radiative transfer equation in some nontrivial coordinate systems." Proceedings of the International Astronomical Union 7, S283 (July 2011): 360–61. http://dx.doi.org/10.1017/s1743921312011428.

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AbstractExplicit expressions for the differential operator of stationary quasi-monochromatic polarized radiative transfer equation in Euclidean space with piecewise homogeneous real part of the effective refractive index are obtained in circular cylindrical, prolate spheroidal, elliptic conical, classic toroidal and simple toroidal coordinate system.
37

Popov, A. M., and R. M. Valiev. "Infinite Linear Systems M/G/\(\infty\) and Multilinear Systems with M/G/n/0 Losses." Current Journal of Applied Science and Technology 42, no. 31 (September 18, 2023): 15–20. http://dx.doi.org/10.9734/cjast/2023/v42i314212.

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The method based on the description of the probabilities of states using a non-stationary Poisson flow allows using elementary reasoning to find not only a stationary, but also a non-stationary distribution of the number of requirements in the system. To find a stationary distribution of the number of requirements in queuing systems (QS), the method of introducing additional variables leading to a piecewise linear Markov process is used. The fact of invariance is shown: the stationary probabilities of pi states in queuing systems (QS) M/G/n/0 depend only on the average service time of the requirement and do not depend on the type of distribution G(x).
38

Дергунов, Олексій Володимирович, and Ганна Вадимівна Мартинюк. "METHOD FOR CHANGE-POINT DETECTION IN PIECEWISE STATIONARY TIME-SERIES." Information systems, mechanics and control, no. 16 (April 10, 2017): 120–27. http://dx.doi.org/10.20535/2219-3804162017100670.

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39

Shamir, G. I., and N. Merhav. "Low-complexity sequential lossless coding for piecewise-stationary memoryless sources." IEEE Transactions on Information Theory 45, no. 5 (July 1999): 1498–519. http://dx.doi.org/10.1109/18.771150.

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40

Sundararajan, Raanju R., and Mohsen Pourahmadi. "Nonparametric change point detection in multivariate piecewise stationary time series." Journal of Nonparametric Statistics 30, no. 4 (August 6, 2018): 926–56. http://dx.doi.org/10.1080/10485252.2018.1504943.

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41

Rho, Yeonwoo, and Xiaofeng Shao. "BOOTSTRAP-ASSISTED UNIT ROOT TESTING WITH PIECEWISE LOCALLY STATIONARY ERRORS." Econometric Theory 35, no. 1 (April 12, 2018): 142–66. http://dx.doi.org/10.1017/s0266466618000038.

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In unit root testing, a piecewise locally stationary process is adopted to accommodate nonstationary errors that can have both smooth and abrupt changes in second- or higher-order properties. Under this framework, the limiting null distributions of the conventional unit root test statistics are derived and shown to contain a number of unknown parameters. To circumvent the difficulty of direct consistent estimation, we propose to use the dependent wild bootstrap to approximate the nonpivotal limiting null distributions and provide a rigorous theoretical justification for bootstrap consistency. The proposed method is compared through finite sample simulations with the recolored wild bootstrap procedure, which was developed for errors that follow a heteroscedastic linear process. Furthermore, a combination of autoregressive sieve recoloring with the dependent wild bootstrap is shown to perform well. The validity of the dependent wild bootstrap in a nonstationary setting is demonstrated for the first time, showing the possibility of extensions to other inference problems associated with locally stationary processes.
42

Last, Michael, and Robert Shumway. "Detecting abrupt changes in a piecewise locally stationary time series." Journal of Multivariate Analysis 99, no. 2 (February 2008): 191–214. http://dx.doi.org/10.1016/j.jmva.2007.06.010.

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43

Zhang, Bo, Guodong Pang, and Bert Zwart. "Refining piecewise stationary approximation for a Markov-regulated fluid queue." ACM SIGMETRICS Performance Evaluation Review 42, no. 2 (September 4, 2014): 15–17. http://dx.doi.org/10.1145/2667522.2667526.

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44

NIZHNIK, LEONID P., IRINA L. NIZHNIK, and MARTIN HASLER. "STABLE STATIONARY SOLUTIONS IN REACTION–DIFFUSION SYSTEMS CONSISTING OF A 1-D ARRAY OF BISTABLE CELLS." International Journal of Bifurcation and Chaos 12, no. 02 (February 2002): 261–79. http://dx.doi.org/10.1142/s0218127402004322.

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In this paper we present the construction of stable stationary solutions in reaction–diffusion systems consisting of a 1-D array of bistable cells with a cubic nonlinearity and with a cubic-like piecewise-linear nonlinearity. Some periodic solutions, kinks, solitons are considered. While it is known that spatial chaos arises in such systems with small coupling constants, we show the existence of spatial chaos for an arbitrary value of the cell coupling constant, in the case of the piecewise-linear nonlinearity. The value of the spatial entropy is found. We also show the existence of stable spatially periodic (pattern) solutions that persist for large coupling constants.
45

Pshenichnov, Sergey, Radan Ivanov, and Maria Datcheva. "Transient Wave Propagation in Functionally Graded Viscoelastic Structures." Mathematics 10, no. 23 (November 29, 2022): 4505. http://dx.doi.org/10.3390/math10234505.

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Transient wave processes in viscoelastic structures built from functionally graded material (FGM) still remain almost unexplored. In this article, the problem of the propagation of nonstationary longitudinal waves in an infinite viscoelastic layer of a FGM with plane–parallel boundaries is considered. The physical and mechanical parameters of the FGM depend continuously on the transverse coordinate, while the wave process propagates along the same coordinate. The viscoelastic properties of the material are taken into account employing the linear integral Boltzmann–Volterra relations. The viscoelastic layer of the FGM is replaced by a piecewise-homogeneous layer consisting of a large number of sub-layers (a package of homogeneous layers), thus approximating the continuous inhomogeneity of the FGM. A solution of a non-stationary dynamic problem for a piecewise-homogeneous layer is constructed and, using a specific example, the convergence of the results with an increase in the number of sub-layers in the approximating piecewise-homogeneous layer is shown. Furthermore, the problem of the propagation of nonstationary longitudinal waves in the cross section of an infinitely long viscoelastic hollow FGM cylinder, whose material properties continuously change along the radius, is also considered. The cylinder composed of the FGM is replaced by a piecewise-homogeneous one, consisting of a large number of coaxial layers, for which the solution of the non-stationary dynamic problem is constructed. For both the layer and the cylinder composed of a viscoelastic FGM, the results of calculating the characteristic parameters of the wave processes for the various initial data are presented. The influence of the viscosity and inhomogeneity of the material on the dynamic processes is demonstrated.
46

Abramowicz, Konrad, and Oleg Seleznjev. "Piecewise-Multilinear Interpolation of a Random Field." Advances in Applied Probability 45, no. 4 (December 2013): 945–59. http://dx.doi.org/10.1239/aap/1386857852.

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We consider a piecewise-multilinear interpolation of a continuous random field on a d-dimensional cube. The approximation performance is measured using the integrated mean square error. Piecewise-multilinear interpolator is defined by N-field observations on a locations grid (or design). We investigate the class of locally stationary random fields whose local behavior is like a fractional Brownian field, in the mean square sense, and find the asymptotic approximation accuracy for a sequence of designs for large N. Moreover, for certain classes of continuous and continuously differentiable fields, we provide the upper bound for the approximation accuracy in the uniform mean square norm.
47

Abramowicz, Konrad, and Oleg Seleznjev. "Piecewise-Multilinear Interpolation of a Random Field." Advances in Applied Probability 45, no. 04 (December 2013): 945–59. http://dx.doi.org/10.1017/s0001867800006716.

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We consider a piecewise-multilinear interpolation of a continuous random field on a d-dimensional cube. The approximation performance is measured using the integrated mean square error. Piecewise-multilinear interpolator is defined by N-field observations on a locations grid (or design). We investigate the class of locally stationary random fields whose local behavior is like a fractional Brownian field, in the mean square sense, and find the asymptotic approximation accuracy for a sequence of designs for large N. Moreover, for certain classes of continuous and continuously differentiable fields, we provide the upper bound for the approximation accuracy in the uniform mean square norm.
48

Barnsley, Michael F., Anca Deliu, and Ruifeng Xie. "Stationary Stochastic Processes and Fractal Data Compression." International Journal of Bifurcation and Chaos 07, no. 03 (March 1997): 551–67. http://dx.doi.org/10.1142/s021812749700039x.

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It is shown that the invariant measure of a stationary nonatomic stochastic process yields an iterated function system with probabilities and an associated dynamical system that provide the basis for optimal lossless data compression algorithms. The theory is illustrated for the case of finite-order Markov processes: For a zero-order process, it produces the arithmetic compression method; while for higher order processes it yields dynamical systems, constructed from piecewise affine mappings from the interval [0, 1] into itself, that may be used to store information efficiently. The theory leads to a new geometrical approach to the development of compression algorithms.
49

Freimanis, Juris. "Polarized Radiative Transfer Equation in Some Geometries of Elliptic Type." Proceedings of the International Astronomical Union 7, S282 (July 2011): 253–54. http://dx.doi.org/10.1017/s1743921311027475.

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AbstractA general method, which allows us to derive explicit expressions for the differential operator of stationary quasi-monochromatic polarized radiative transfer equation in Euclidean space, with piecewise homogeneous real part of the effective refractive index, is applied to ellipsoidal, oblate spheroidal, prolate spheroidal and elliptic conical coordinate systems.
50

Ogorodnikov, Vasily A., and Olga V. Sereseva. "Probabilistic properties of non-Gaussian piecewise-linear processes on Poisson flows with independent random values at points of flow." Russian Journal of Numerical Analysis and Mathematical Modelling 33, no. 1 (February 23, 2018): 55–64. http://dx.doi.org/10.1515/rnam-2018-0005.

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Abstract The paper is focused on study of non-stationary piecewise-linear processes on Poisson point flows with independent identically distributed random variables at support points. An approach to calculate the correlation function of the process on the base of the total probability formula is considered. A general expression for the correlation function of a non-stationary process is obtained. Particular cases are considered. Using the method of direct simulation, it is shown numerically that the correlation function of the process has a point of inflection.

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