Results 31 to 40 of about 4,727,432 (231)
International Journal of Interactive Multimedia and Artificial Intelligence, 2022 Sampling-based motion planning in the field of robot motion planning has provided an effective approach to finding path for even high dimensional configuration space and with the motivation from the concepts of sampling based-motion planners, this paper
Lhilo Kenye, Rahul Kala
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On Some Further Generalizations of Strong Convergence in Probabilistic Metric Spaces Using Ideals
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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$I^K_ν$-Convergence of functions in probabilistic normed spaces
, 2023 In this paper we study $I^K$-convergence of functions with respect to probabilistic norm $ν$ which is a generalization of $I^*_ν$-convergence in probabilistic norm spaces. We also study on $I^K$-Cauchy functions and $I^K$-limit points with respect to probabilistic norm $ν$ in the same space.
Banerjee, Amar Kumar, Paul, Mahendranath
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Generalized ?m-Statistical Convergence in Probabilistic Normed Space
, 2011 In this paper we define the concepts of S-Delta m(lambda) -statistical convergence and S-Delta m(lambda) -statistically Cauchy in probabilistic normed space and give some results. The main purpose of this paper is to generalize the results on statistical
Esi, Ayhan, Ozdemir, M. Kemal
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Some Results on Best Proximity Points of Cyclic Contractions in Probabilistic Metric Spaces
Journal of Function Spaces, 2015 This paper investigates properties of convergence of distances of p-cyclic contractions on the union of the p subsets of an abstract set X defining probabilistic metric spaces and Menger probabilistic metric spaces as well as the characterization of ...
Manuel De la Sen, Erdal Karapınar
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Strong and weak convergences in 2-probabilistic normed spaces
Advances in the Theory of Nonlinear Analysis and its Application, 2021 In this paper, we have introduced the notions of strong and weak convergences in 2-probabilistic normed spaces (2-PN spaces) and established some of its properties. Later, we have defined the strong and weak boundedness of a linear map between two 2-PN spaces and proved a necessary and sufficient condition for the linear map between two 2-PN spaces to ...
Harikrishnan PANACKAL +3 more
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Probabilistic hyperspace analogue to language [PDF]
, 2005 Song and Bruza introduce a framework for Information Retrieval(IR) based on Gardenfor's three tiered cognitive model; Conceptual Spaces. They instantiate a conceptual space using Hyperspace Analogue to Language (HAL to generate higher order concepts ...
Azzopardi, L. +5 more
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On ideal convergence in probabilistic normed spaces
Mathematica Slovaca, 2011 Abstract An interesting generalization of statistical convergence is I-convergence which was introduced by P.Kostyrko et al [KOSTYRKO,P.—ŠALÁT,T.—WILCZYŃSKI,W.: I-Convergence, Real Anal. Exchange 26 (2000–2001), 669–686]. In this paper, we define and study the concept of I-convergence, I*-convergence, I-limit points and I-cluster points ...
Mursaleen, M., Mohiuddine, S. A.
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On Strong A-statistical Convergence in Probabilistic Metric Spaces
, 2022 In this paper we study some basic properties of strong A-statistical convergence and strong A-statistical Cauchyness of sequences in probabilistic metric spaces not done earlier. We also study some basic properties of strong A-statistical limit points and strong A-statistical cluster points of a sequence in a probabilistic metric space. Further we also
Malik, Prasanta, Das, Samiran
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Solution Representation Learning in Multi-Objective Transfer Evolutionary Optimization
IEEE Access, 2021 This paper presents a first study on solution representation learning for inducing greater alignment and hence positive transfers between distinct multi-objective optimization tasks that bear discrepancies in their original search spaces.
Ray Lim +4 more
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