non-stationary stochastic process
Determination of non-stationary stochastic processes compatible with seismic response/design spectra
... a stochastic formulation originally proposed by Spanos and Vargas Loli (1985) to address the issue of deriving a non-stationary stochastic process compatible with a given (target) ...
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Joint time-frequency representation of simulated earthquake accelerograms via the adaptive chirplet transform
... random process, the numerical results in- dicate slight frequency-dependent deviations of the actual modulating envelopes from the adopted theo- retical ...of non-stationary data as realiza- tions of ...
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Derivation of response spectrum compatible non-stationary stochastic processes relying on Monte Carlo-based peak factor estimation
... simulated time-histories compatible with power spectra which are consistent with the design spectrum (see e.g. Preumont 1985a, Giaralis and Spanos 2009, Cacciola 2010, Martinelli et al. 2011, and references therein). The ...
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A stochastic dynamics approach for response spectrum analysis of bilinear systems using time-dependent equivalent linear properties
... A stochastic averaging approach has been used in conjunction with non-stationary response spectrum compatible random processes to derive time-varying ELPs, for bilinear hysteretic oscillators subject ...
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Non Stationary Stochastic Volatility Model for Dynamic Feedback and Skewness
... decades. Stochastic volatility (SV) model ((Taylor 1982)) has been one of the key instruments to address this ...auto-regressive process to account for the volatility ...
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Modelling of Non-Stationary Mobile Radio Channels Incorporating the Brownian Mobility Model With Drift
... (BM) process with drift to model the mobile radio channel under non-stationary ...BM process with drift ...a non-centred one-ring scattering model in which the local scatterers are ...
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The Variance Profile
... a stationary stochastic process. It is a continuous and non-decreasing function of the power parameter, p, which returns the minimum of the spectrum (p → −∞ ), the interpolation error variance ...
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Robust Extrapolation Problem for Stochastic Processes with Stationary Increments
... of stochastic processes is an important part of the theory of stochastic pro- ...ary stochastic processes were developed by Kolmogorov [1], Wiener[2], Yaglom [3, ...of non-stationary ...
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Computationally Efficient Estimation of Non-stationary Gaussian Process Models for Large Spatial Data.
... two non-stationary Gaussian process models in the case of large spatial ...described stochastic score approximations in these non-stationary models for parameter ...are ...
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A novel stochastic linearization framework for seismic demand estimation of hysteretic MDOF systems subject to linear response spectra
... economical stochastic dynamics framework to estimate the peak inelastic response of yielding structures modelled as nonlinear multi degree- of-freedom (DOF) systems subject to a given linear response spectrum ...
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SHIFT OPERATOR FOR PERIODICALLY CORRELATED PROCESSES
... any stationary stochastic pro- cess has a bounded shift and that it is a unitary ...a non-stationary process as we saw above the shift may not even exist and in order for a ...
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Non Stationary Random Process for Large Scale Failure and Recovery of Power Distribution
... We first formulate, from bottom up, an entire life cycle of large-scale failure and recovery. The problem for- mulation begins at the finest level of network nodes based on temporal-spatial stochastic processes. ...
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Stationary and non-stationary solutions of the evolution equation for neutrino in matter
... the stationary states and the spin-flavor coherent states of the neutrino are ...the stationary states with coefficients, which depend on the mixing angle in ...
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Auto tail dependence coefficients for stationary solutions of linear stochastic recurrence equations and for GARCH(1,1)
... Goldie [5] has given an alternative proof of Kesten’s theorem in the scalar case which provides an explicit formula for the constant c (in terms of the stationary distribution). The precise value of this constant ...
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Time Frequency Domain Characterization of Stationary and Non stationary Signals
... The STFT employs a time window g(t) of certain duration that is centered at time τ. For each specific time τ, the time localized Fourier transform is calculated. Then this window moves along the time axis and again the ...
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Probabilistic Framework For A Time Series
... be stationary in the wide sense if [5], Where Q ...as non- stationary whenever it is not stationary (in either sense), a usual approach is to identify and isolate the ...
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Methods of proving uniqueness of stationary distributions for stochastic PDEs
... We wish to show that, for 0 > 9C1 there is a unique translation invariant station ary distribution satisfying a certain mixing property which is “living”, i.e. gives zero probability to the zero configuration. Since ...
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Model Diatom Population by Branching Stochastic Processes
... capable of dividing and every particle is of zero age at birth, that is to say G (0)=G (0+)=0. In this case of right continuity at the zero point of the d.f., the multidimensional g.f. is more suitable for research and ...
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Quantitative stability analysis of stochastic generalized equations
... of stationary points of a number of stochastic optimization ...of stochastic optimization (see ...of stochastic generalized equations where the true probability measure is approximated through ...
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Time-Frequency Domain Characterization of Stationary and Non stationary Signals
... Fourier transform is actually the convolution of signal x(t) or x(n) with sine and cosine function as understood from above equations. This convolution actually measures the similarity between signal x(t) and ...
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