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[PDF] Top 20 Estimation of Space Deformation Model for Non-stationary Random Functions

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Estimation of Space Deformation Model for Non-stationary Random Functions

Estimation of Space Deformation Model for Non-stationary Random Functions

... Abstract Stationary Random Functions have been successfully applied in geostatistical applications for ...assumption of a homogeneous spatial dependence structure across the entire ... Voir le document complet

18

A Generalized Convolution Model and Estimation for Non-stationary Random Functions

A Generalized Convolution Model and Estimation for Non-stationary Random Functions

... set of 67 ...terms of modelling a new model for second order non-stationary Random ...new model generalizes the classical convolution model and provides ... Voir le document complet

25

Brownian motion on stationary random manifolds

Brownian motion on stationary random manifolds

... measurable functions f : M → R. In order for the above equation to make sense one needs to know that the inner integral on the right hand side is Borel measurable on the Gromov ...proof of the ... Voir le document complet

113

Pointwise smoothness of space-filling functions

Pointwise smoothness of space-filling functions

... spectrum of singularities of signals obtained through the registering of real-life data cannot be estimated in the case of multifractal signals; indeed the determination of their Hölder ... Voir le document complet

19

Deviation inequalities for separately Lipschitz functionals of iterated random functions

Deviation inequalities for separately Lipschitz functionals of iterated random functions

... transform of the dominating random variables G X 1 (X 1 ) and G ε (ε k ) satisfy the Cram´er condition, we obtain the following proposition similar to that of Liu and Watbled [20] under the ... Voir le document complet

25

Upper functions for $\mathbb{L}_{p}$-norms of Gaussian random fields

Upper functions for $\mathbb{L}_{p}$-norms of Gaussian random fields

... kind of results we expect to obtain. We provide with upper functions and the inequality ...bound for an upper function and discuss its ...proofs of all presented results are straightforward ... Voir le document complet

39

Exploring the Space of IR Functions

Exploring the Space of IR Functions

... the space of scoring functions, they are still limited in two aspects: first, they usually assume that the IR scoring function takes a particular form ...parameters of the function given a ... Voir le document complet

13

Stationary solutions with vacuum for a one-dimensional chemotaxis model with non-linear pressure

Stationary solutions with vacuum for a one-dimensional chemotaxis model with non-linear pressure

... movement of cells, bacteria or other microorganisms following the gradient of a chemical concentration, known as chemoattractant, has been widely studied in mathematics in the last two decades [15, ... Voir le document complet

38

Locally stationary long memory estimation

Locally stationary long memory estimation

... scheme of one-sided smoothing weights, adapted to the end point of the observation ...The model studied in this paper arises naturally in the now long history of time series mod- elling in ... Voir le document complet

33

An approximation result for special functions with bounded deformation

An approximation result for special functions with bounded deformation

... Some of these issues are addressed in [3, 18, 16, 21, 17], for variants of this problem (scalar versions, topological restrictions on the cracks, nonlinear ...case of linearized elasticity, a ... Voir le document complet

22

GENFIELD: A parallel software for the generation of stationary Gaussian random fields

GENFIELD: A parallel software for the generation of stationary Gaussian random fields

... studies of waste storage in deep geological media Sand and gravel deposits in Switzerland, Gelhar [1993] permeability (md) General algorithm in 1D Algorithm when no padding is required ... Voir le document complet

2

Optimal Embedded Sensor Placement for Spatial Variability Assessment of Stationary Random Fields

Optimal Embedded Sensor Placement for Spatial Variability Assessment of Stationary Random Fields

... variability of material properties or defaults; however, there are still various challenges for their characterization and ...in space and time for spatial variability characterization ... Voir le document complet

17

Diffusion in a locally stationary random environment

Diffusion in a locally stationary random environment

... ticity of ¯ A ...law of the process X ε converges for (almost) every fixed realization ω of the random medium? The main difficulty to prove such a result actually lies in establishing a ... Voir le document complet

25

CUTOFF FOR NON-BACKTRACKING RANDOM WALKS ON SPARSE RANDOM GRAPHS

CUTOFF FOR NON-BACKTRACKING RANDOM WALKS ON SPARSE RANDOM GRAPHS

... problem of singling out abstract conditions under which the cutoff phe- nomenon occurs, without necessarily pinpointing its precise location, has drawn considerable ...criterion for reversible chains, known ... Voir le document complet

20

An open microscopic model of heat conduction: evolution and non-equilibrium stationary states

An open microscopic model of heat conduction: evolution and non-equilibrium stationary states

... system for which conserved quantities evolve macroscopically in the same diffusive time scale, and their macroscopic evolution is governed by a system of coupled diffusive ...chain of coupled rotors, ... Voir le document complet

33

An open microscopic model of heat conduction: evolution and non-equilibrium stationary states

An open microscopic model of heat conduction: evolution and non-equilibrium stationary states

... densities of these quantities may evolve at different time scales, and their interaction can give rise to a superdiffusive energy behaviour, particularly when the spatial dimension of the system equals ... Voir le document complet

24

Smooth-transition regression models for non-stationary extremes

Smooth-transition regression models for non-stationary extremes

... regression model, useful for handling the time- varying effect of risk factors on the severity distribution of financial ...This model has the advantages of accounting explicitly ... Voir le document complet

43

Riccati Observers for the non-stationary PnP problem

Riccati Observers for the non-stationary PnP problem

... Observers for the non-stationary PnP problem Tarek Hamel and Claude Samson Abstract— This paper revisits the problem of estimating the pose (position and orientation) of a body in 3D ... Voir le document complet

17

A Bayesian non-parametric hidden Markov random model for hemodynamic brain parcellation

A Bayesian non-parametric hidden Markov random model for hemodynamic brain parcellation

... assumption of HRF shape invariance within each parcel, whereas reliability should guarantee that parcels are large enough to ensure reliable HRF estimation and detection ...number of recent ... Voir le document complet

16

A Bayesian non-parametric hidden Markov random model for hemodynamic brain parcellation

A Bayesian non-parametric hidden Markov random model for hemodynamic brain parcellation

... detection estimation model addresses this issue by inferring the parcels from fMRI ...number of parcels through an initial mask for ...mixture model combined with a hidden Markov ... Voir le document complet

16

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