Results 11 to 20 of about 4,727,432 (231)
T-regular probabilistic convergence spaces [PDF]
Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics, 1998 AbstractA probabilistic convergence structure assigns a probability that a given filter converges to a given element of the space. The role of the t-norm (triangle norm) in the study of regularity of probabilistic convergence spaces is investigated. Given a probabilistic convergence space, there exists a finest T-regular space which is coarser than the
Minkler, J., Minkler, G., Richardson, G.
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Probabilistic convergence spaces [PDF]
Journal of the Australian Mathematical Society. Series A. Pure Mathematics and Statistics, 1996 AbstractA basic theory for probabilistic convergence spaces based on filter convergence is introduced. As in Florescu's previous theory of probabilistic convergence structures based on nets, one is able to assign a probability that a given filter converges to a given point.
Richardson, G. D., Kent, D. C.
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Convergence in probabilistic semimetric spaces
Rocky Mountain Journal of Mathematics, 1988 A probabilistic semimetric space (S,F) is a set S together with a function F defined on \(S\times S\) with values in the space \(\Delta^+\), which is a space of real-valued functions, satisfying some weak assumptions resembling those for a metric except for the triangular inequality.
Richardson, G. D.
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Probabilistic approach spaces [PDF]
Mathematica Bohemica, 2017 We study a probabilistic generalization of Lowen's approach spaces. Such a probabilistic approach space is defined in terms of a probabilistic distance which assigns to a point and a subset a distance distribution function.
Gunther Jäger
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Probabilistic analysis of vantage point trees
Modern Stochastics: Theory and Applications, 2021 Probabilistic properties of vantage point trees are studied. A vp-tree built from a sequence of independent identically distributed points in ${[-1,\hspace{0.1667em}1]^{d}}$ with the ${\ell _{\infty }}$-distance function is considered.
Vladyslav Bohun
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Strong $I^K$-Convergence in Probabilistic Metric Spaces
Iranian Journal of Mathematical Sciences and Informatics, 2022 12 pages.
Banerjee, A. K., Paul, M.
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Quantitative estimate of the overdamped limit for the Vlasov–Fokker–Planck systems
Partial Differential Equations in Applied Mathematics, 2021 This note adapts a probabilistic approach to establish a quantified estimate of the overdamped limit for the Vlasov–Fokker–Planck equation towards the aggregation–diffusion equation, which in particular includes cases of the Newtonian type singular ...
Hui Huang
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MB-RRT: An Inverse Kinematics Solver of Reduced Dimension
IEEE Access, 2021 The evolution of manipulator robots has increased the complexity of their models and applications, requiring that the inverse kinematics (IK) methods integrated into their control systems to have features such as fast convergence, completeness, low ...
Matheus C. Santos +5 more
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Statistical Convergence of Double Sequences on Probabilistic Normed Spaces [PDF]
International Journal of Mathematics and Mathematical Sciences, 2007 The concept of statistical convergence was presented by Steinhaus in 1951. This concept was extended to the double sequences by Mursaleen and Edely in 2003. Karakus has recently introduced the concept of statistical convergence of ordinary (single) sequence on probabilistic normed spaces.
Sevda Karakus, Kamil Demirci
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IEEE Access, 2023 Extended target tracking estimates the centroid and shape of the target in space and time. In various situations where extended target tracking is applicable, the presence of multiple targets can lead to interference, particularly when they maneuver ...
Behzad Akbari +3 more
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