Results 21 to 30 of about 1,718,862 (286)
On limit theorems for random fields
A complete separable metric space of functions defined on the positive quadrant of the plane is constructed. The characteristic property of these functions is that at every point x there exist two lines intersecting at this point such that limits limy→x ...
Rimas Banys
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Associative Hierarchical Random Fields
This paper makes two contributions: the first is the proposal of a new model-The associative hierarchical random field (AHRF), and a novel algorithm for its optimization; the second is the application of this model to the problem of semantic segmentation.
Ladický, L +3 more
openaire +2 more sources
This paper presents the probabilistic analysis of landslides in spatially variable soil deposits, modeled by a stochastic framework which integrates the random field theory with generalized interpolation material point method (GIMP).
MA Guo-tao +3 more
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This paper presents an efficient method and its usage for the three-dimensional random bearing capacity evaluation for square and rectangular footings.
Chwała Marcin
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Random Galois extensions of Hilbertian fields [PDF]
Let L be a Galois extension of a countable Hilbertian field K.
Bary-Soroker, Lior, Fehm, Arno
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Large scale random fields generation using localized Karhunen–Loève expansion
In this paper the generation of random fields when the domain is much larger than the characteristic correlation length is made using an adaptation of the Karhunen–Loève expansion (KLE).
Alfonso M. Panunzio +2 more
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Influence of Yield Strength Variability over Cross-Section to Steel Beam Load-Carrying Capacity
Authors of article analysed influence of variability of yield strength over cross-section of hot rolled steel member to its load-carrying capacity. In calculation models, the yield strength is usually taken as constant.
J. Kala, Z. Kala
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Optimal Nonlinear Prediction of Random Fields on Networks [PDF]
It is increasingly common to encounter time-varying random fields on networks (metabolic networks, sensor arrays, distributed computing, etc.).This paper considers the problem of optimal, nonlinear prediction of these fields, showing from an information ...
Cosma Rohilla Shalizi
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Topology Optimisation under Uncertainties with Neural Networks
Topology optimisation is a mathematical approach relevant to different engineering problems where the distribution of material in a defined domain is distributed in some optimal way, subject to a predefined cost function representing desired (e.g ...
Martin Eigel +2 more
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Some remarks on selfnormalization for a simple spatial autoregressive model
In the paper I continue investigations on the self-normalization of simple autoregressive field Xt,s = aXt−1,s + bXt,s−1 + εt,s started in [5]. And extend previous results when the variance of the innovations of the process above are not finite.
Romas Zovė
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