Results 211 to 220 of about 28,086 (261)
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Perfect simulation in stochastic geometry
Pattern Recognition, 1999Simulation plays an important role in stochastic geometry and related fields, because all but the simplest random set models tend to be intractable to analysis. Many simulation algorithms deliver (approximate) samples of such random set models, for example by simulating the equilibrium distribution of a Markov chain such as a spatial birth-and-death ...
Wilfrid Kendall
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Models of stochastic geometry ? A survey
ZOR Zeitschrift f� Operations Research Methods and Models of Operations Research, 1993Summary: This paper discusses some models of stochastic geometry which are of potential interest for operations research. These are the Boolean model, a certain model for random compact sets and marked point processes. The Boolean model is a generalization of the well-known queueing system \(M/G/\infty\).
Dietrich Stoyan, Günter Lippmann
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Stochastic and Integral Geometry
Probability and Its Applications, 2008Rolf Schneider, Wolfgang Weil
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Stochastic Geometry and Its Applications.
Journal of the American Statistical Association, 198823. Stochastic Geometry and its Applications. By D. Stoyan, W. S. Kendall and J. Mecke. ISBN 0 471 90519 4. Wiley, 1987. 345p. £23.50. (Wiley Series in Probability and Mathematical Statistics. A co‐production with Akademie‐Verlag, GDR.)
B. D. Ripley +3 more
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On the Stochastic Geometry of Growth
2003The pioneering book by D’Arcy Thompson, entitled “On Growth and Form” [13], was perhaps the first to consider applying (deterministic) mathematics to problems in biology, in particular those problems associated with the growth of biological objects.
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COMPUTER VISION AND STOCHASTIC GEOMETRY
1990An approach from the stochastic geometry viewpoint to the problem of forming recognition feasures invariant to objects' rotations and translation is considered. Technical vision simple applied systems' structure is discussed.
Nikolai G. Fedotov, Michael E. Larin
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1992
Abstract So far we have considered random countable subsets of spaces S which have always been subsets of !Rd for some dimension d. The theory is, however, much more general, and applies to random structures which look quite different from the irregular array of isolated points depicted in Fig. 1.1.
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Abstract So far we have considered random countable subsets of spaces S which have always been subsets of !Rd for some dimension d. The theory is, however, much more general, and applies to random structures which look quite different from the irregular array of isolated points depicted in Fig. 1.1.
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Stochastic differential geometry: An introduction
Acta Applicandae Mathematicae, 1987This is a survey on the relations between asymptotic properties of semi- martingales and, in particular, of Brownian motion on a Riemannian manifold on the one hand and curvature properties of the manifold on the other hand. Following a brief description of real-valued semimartingales and of some essentials of calculus on manifolds, an introduction to ...
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Stochastic Differential Geometry
2021Semi-martingales, bilinear forms, pull-back, covariation process, semimartingale integral, connection, chain rule, differential operators and Christoffel symbols, martingale criteria, induced connections, affine and convex maps, geodesics and martingale criteria, local drift and diffusion rates, sub-manifolds and projection, diffusions, Riemannian ...
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Stochastic Geometry for Wireless Networks
2012Covering point process theory, random geometric graphs and coverage processes, this rigorous introduction to stochastic geometry will enable you to obtain powerful, general estimates and bounds of wireless network performance and make good design choices for future wireless architectures and protocols that efficiently manage interference effects ...
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