Results 291 to 300 of about 15,642,613 (349)
Some of the next articles are maybe not open access.
Mechanical systems and signal processing, 2018
Cross-correlated random field samples (RFSs) of engineering quantities (e.g., mechanical properties of materials) are often needed for stochastic analysis of structures when cross-correlation between engineering quantities and spatial/temporal auto ...
Tengyuan Zhao, Yu Wang
semanticscholar +1 more source
Cross-correlated random field samples (RFSs) of engineering quantities (e.g., mechanical properties of materials) are often needed for stochastic analysis of structures when cross-correlation between engineering quantities and spatial/temporal auto ...
Tengyuan Zhao, Yu Wang
semanticscholar +1 more source
Information Sciences, 1975
Abstract The fundamental properties of complex random fields are derived directly in an n-dimensional setting and are not inferred as generalizations of the one-dimensional case. In particular, fields with orthogonal increments and stochastic integrals with respect to such fields are defined and their elementary properties analyzed.
openaire +2 more sources
Abstract The fundamental properties of complex random fields are derived directly in an n-dimensional setting and are not inferred as generalizations of the one-dimensional case. In particular, fields with orthogonal increments and stochastic integrals with respect to such fields are defined and their elementary properties analyzed.
openaire +2 more sources
2006 3rd International Symposium on Voronoi Diagrams in Science and Engineering, 2006
We propose a random field regarded as a generalization of Voronoi diagrams for the case where the positions of generators are distributed probabilistically. Our approach is a kind of stochastic approaches to Voronoi diagrams; however our definition is different from usual random Voronoi diagrams such as Poisson Voronoi diagrams.
openaire +1 more source
We propose a random field regarded as a generalization of Voronoi diagrams for the case where the positions of generators are distributed probabilistically. Our approach is a kind of stochastic approaches to Voronoi diagrams; however our definition is different from usual random Voronoi diagrams such as Poisson Voronoi diagrams.
openaire +1 more source
Hidden Conditional Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007We present a discriminative latent variable model for classification problems in structured domains where inputs can be represented by a graph of local observations. A hidden-state Conditional Random Field framework learns a set of latent variables conditioned on local features. Observations need not be independent and may overlap in space and time.
Ariadna Quattoni +4 more
openaire +2 more sources
Advances in Applied Probability, 1978
is of great importance in many applications. For example, if we consider a geographical map and denote height by X(t) where t is the set of geographical coordinates, Z(S) is the height of the highest mountain in the area S. In general, it is not possible to make any exact useful statements about the distribution of Z(S), and one must have recourse to ...
openaire +1 more source
is of great importance in many applications. For example, if we consider a geographical map and denote height by X(t) where t is the set of geographical coordinates, Z(S) is the height of the highest mountain in the area S. In general, it is not possible to make any exact useful statements about the distribution of Z(S), and one must have recourse to ...
openaire +1 more source
Computer Graphics Forum, 1985
AbstractThis paper presents an algorithm for random fields generation. The main idea of the paper is an improvement of the recursive technique presented by A. Fournier, D. Fussel and L. Carpenter in [4]. In order to ensure the continuity constraints on the boundaries of the cells generated at different stages of the algorithm, we show that it is ...
openaire +1 more source
AbstractThis paper presents an algorithm for random fields generation. The main idea of the paper is an improvement of the recursive technique presented by A. Fournier, D. Fussel and L. Carpenter in [4]. In order to ensure the continuity constraints on the boundaries of the cells generated at different stages of the algorithm, we show that it is ...
openaire +1 more source
Structures in random fields: Gaussian fields
Physical Review A, 1992We present two alternative methods for evaluating the probability densities of structures defined by d degrees of freedom in random fields. For Gaussian random fields, both differentiable and nondifferentiable, the application of these methods is considered in detail.
openaire +2 more sources
Random fields on random graphs
Advances in Applied Probability, 1992The distribution (1) used previously by the author to represent polymerisation of several types of unit also prescribes quite general statistics for a random field on a random graph. One has the integral expression (3) for its partition function, but the multiple complex form of the integral makes the nature of the expected ...
openaire +2 more sources
Skew-Gaussian random field [PDF]
Journal of Computational and Applied Mathematics, 2009 In this article, we introduce the concept of skewness to the Gaussian random field theory by defining a new two-dimensional non-Gaussian random field called skew-Gaussian random field.
Al-Rawwash, M.Y., Alodat, M.T.
exaly +2 more sources