Results 11 to 20 of about 18,707 (285)
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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On Some Further Generalizations of Strong Convergence in Probabilistic Metric Spaces Using Ideals [PDF]
Abstract and Applied Analysis, 2013 Following the line of (Das et al., 2011, Savas and Das, 2011), we make a new approach in this paper to extend the notion of strong convergence and more general strong statistical convergence (Şençimen and Pehlivan, 2008) using ideals and introduce the ...
Pratulananda Das +3 more
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Ideal Convergence of Random Variables [PDF]
Journal of Function Spaces and Applications, 2013 The aim of this paper is to introduce and study the notion of I-convergence of random variables via probabilistic norms. Furthermore, we introduce I-convergence in Lp space and establish some interesting results.
B. Hazarika, S. A. Mohiuddine
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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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Some new lacunary statistical convergence with ideals
Journal of Inequalities and Applications, 2017 In this paper, the idea of lacunary I λ $I_{\lambda}$ -statistical convergent sequence spaces is discussed which is defined by a Musielak-Orlicz function.
Adem Kilicman, Stuti Borgohain
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µ-Statistically convergent function sequences in probabilistic normed linear spaces
Proyecciones (Antofagasta), 2019 In this article, we introduce the concept of µ-statistical convergence and µ-density convergence of sequences of functions defined on a compact subset D of the probabilistic normed space (X, N, ∗), where µ is a finitely additive two valued measure. In particular, we introduce the notions of µ-statistical uniform convergence as well as µ-statistical ...
Mausumi Sen +2 more
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Statistical convergence in strong topology of probabilistic normed spaces [PDF]
, 2008 Following the concept of statistical convergence, we define and study statistical analog concepts of convergence and Cauchy's sequence on a probabilistic normed space that is endowed with a strong topology. Some important properties of statistical convergence have been extended in this new setting.
Lafuerza Guillén, Bernardo +1 more
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Quantale-valued Cauchy tower spaces and completeness
Applied General Topology, 2021 Generalizing the concept of a probabilistic Cauchy space, we introduce quantale-valued Cauchy tower spaces. These spaces encompass quantale-valued metric spaces, quantale-valued uniform (convergence) tower spaces and quantale-valued convergence tower ...
Gunther Jäger, T. M. G. Ahsanullah
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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 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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