Results 221 to 230 of about 7,133 (253)
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On φ-Contractions in Probabilistic and Fuzzy Metric Spaces
Fuzzy Sets and Systems, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jin-Xuan Fang
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On Probabilistic ψ-Contractions in Menger Probabilistic Metric Spaces
Fuzzy Sets and Systems, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dingwei Zheng, Pei Wang
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Strong Statistical Convergence in Probabilistic Metric Spaces
Stochastic Analysis and Applications, 2008 In this article, we introduce the concepts of strongly statistically convergent sequence and strong statistically Cauchy sequence in a probabilistic metric (PM) space endowed with the strong topology, and establish some basic facts. Next, we define the strong statistical limit points and the strong statistical cluster points of a sequence in this space
Serpil Pehlivan
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Probabilistic tracking in a metric space
Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2002A new exemplar-based, probabilistic paradigm for visual tracking is presented. Probabilistic mechanisms are attractive because they handle fusion of information, especially temporal fusion, in a principled manner. Exemplars are selected representatives of raw training data, used here to represent probabilistic mixture distributions of object ...
Kentaro Toyama, Andrew Blake 0001
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Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kentaro Toyama, Andrew Blake 0001
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2001
In 1942 K. Menger introduced the notion of a statistical metric space as a natural generalization of the notion of a metric space (M, d) in which the distance d(p, q) (p, q ∈ M) between p and q is replaced by a distribution function F p, q ∈ Δ+. F p,q (x) can be interpreted as the probability that the distance between p and q is less than x.
Olga Hadžić, Endre Pap
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In 1942 K. Menger introduced the notion of a statistical metric space as a natural generalization of the notion of a metric space (M, d) in which the distance d(p, q) (p, q ∈ M) between p and q is replaced by a distribution function F p, q ∈ Δ+. F p,q (x) can be interpreted as the probability that the distance between p and q is less than x.
Olga Hadžić, Endre Pap
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2003
This is a presentation without proofs of the key facts about the topology of Probabilistic Metric spaces, Probabilistic Normed spaces and Probabilistic Inner Product spaces.
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This is a presentation without proofs of the key facts about the topology of Probabilistic Metric spaces, Probabilistic Normed spaces and Probabilistic Inner Product spaces.
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Complete probabilistic metric spaces
Zeitschrift f�r Wahrscheinlichkeitstheorie und Verwandte Gebiete, 1971Menger [4] initiated the study of probabilistic metric spaces in 1942. A probabilistic metric space (briefly a PM space) is a space in which the "distance" between any two points is a probability distribution function. These spaces are assumed to satisfy axioms which are quite similar to the axioms satisfied in an ordinary metric space.
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Probabilistic enhancement of approximate indexing in metric spaces
Information Systems, 2013Abstract Some approximate indexing schemes have been recently proposed in metric spaces which sort the objects in the database according to pseudo-scores. It is known that (1) some of them provide a very good trade-off between response time and accuracy, and (2) probability-based pseudo-scores can provide an optimal trade-off in range queries if the ...
Takao Murakami +3 more
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On Generalized Contractions in Probabilistic Metric Spaces
AIP Conference Proceedings, 2011In this paper, we introduce a generalized concept of contraction in probabilistic metric spaces. Coincidence and fixed point theorems for mappings with this contraction property are proved and particular cases are analyzed.
Ioan Goleţ +5 more
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