Karakus, S.; Demırcı, K. Statistical convergence of double sequences on probabilistic normed spaces. (English) Zbl 1147.54016 Int. J. Math. Math. Sci. 2007, Article ID 14737, 11 p. (2007). The authors discuss problems of statistical convergence for double sequences with respect to the probabilistic norm. This notion is introduced as a generalization of the concept of statistical convergence for double sequences [M. Mursaleen and O. H. H. Edely, J. Math. Anal. Appl. 288, No. 1, 223–231 (2003; Zbl 1032.40001)]. Similarly the authors define the notion of statistical Cauchy double sequences with respect to the given probabilistic norm. The authors demonstrate also that statistical convergence of double sequences on probabilistic normed spaces has some arithmetical properties similar to properties of the usual convergence for real points. Reviewer: A. Świerniak (Gliwice) Cited in 1 ReviewCited in 16 Documents MSC: 54E70 Probabilistic metric spaces 54A20 Convergence in general topology (sequences, filters, limits, convergence spaces, nets, etc.) 46S50 Functional analysis in probabilistic metric linear spaces 40A05 Convergence and divergence of series and sequences Keywords:statistical convergence; probabilistic normed spaces; double sequences Citations:Zbl 1032.40001 PDF BibTeX XML Cite \textit{S. Karakus} and \textit{K. Demırcı}, Int. J. Math. Math. Sci. 2007, Article ID 14737, 11 p. (2007; Zbl 1147.54016) Full Text: DOI References: [1] K. Menger, “Statistical metrics,” Proceedings of the National Academy of Sciences of the United States of America, vol. 28, no. 12, pp. 535-537, 1942. · Zbl 0063.03886 [2] G. Constantin and I. Istr\ua\ctescu, Elements of Probabilistic Analysis with Applications, vol. 36 of Mathematics and Its Applications (East European Series), Kluwer Academic Publishers, Dordrecht, The Netherlands, 1989. · Zbl 0694.60002 [3] B. Schweizer and A. Sklar, “Statistical metric spaces,” Pacific Journal of Mathematics, vol. 10, pp. 313-334, 1960. · Zbl 0091.29801 [4] B. Schweizer and A. Sklar, Probabilistic Metric Spaces, North-Holland Series in Probability and Applied Mathematics, North-Holland, New York, NY, USA, 1983. · Zbl 0546.60010 [5] S. Karakus, “Statistical convergence on probabilistic normed spaces,” Mathematical Communications, vol. 12, pp. 11-23, 2007. · Zbl 1158.40001 [6] A. Aghajani and K. Nourouzi, “Convex sets in probabilistic normed spaces,” Chaos, Solitons & Fractals, 2006. · Zbl 1138.46050 [7] H. Steinhaus, “Sur la convergence ordinaire et la convergence asymptotique,” Colloquium Mathematicum, vol. 2, pp. 73-74, 1951. [8] H. Fast, “Sur la convergence statistique,” Colloquium Mathematicum, vol. 2, pp. 241-244, 1951. · Zbl 0044.33605 [9] J. S. Connor, “The statistical and strong p-Cesàro convergence of sequences,” Analysis, vol. 8, no. 1-2, pp. 47-63, 1988. · Zbl 0653.40001 [10] J. S. Connor, “A topological and functional analytic approach to statistical convergence,” in Analysis of Divergence (Orono, Me, 1997), Appl. Numer. Harmon. Anal., pp. 403-413, Birkhäuser, Boston, Mass, USA, 1999. · Zbl 0915.40002 [11] J. A. Fridy, “On statistical convergence,” Analysis, vol. 5, no. 4, pp. 301-313, 1985. · Zbl 0588.40001 [12] A. Pringsheim, “Zur theorie der zweifach unendlichen zahlenfolgen,” Mathematische Annalen, vol. 53, no. 3, pp. 289-321, 1900. · JFM 31.0249.01 [13] J. Christopher, “The asymptotic density of some k-dimensional sets,” The American Mathematical Monthly, vol. 63, no. 6, pp. 399-401, 1956. · Zbl 0070.04101 [14] M. Mursaleen and O. H. H. Edely, “Statistical convergence of double sequences,” Journal of Mathematical Analysis and Applications, vol. 288, no. 1, pp. 223-231, 2003. · Zbl 1032.40001 [15] F. Móricz, “Statistical convergence of multiple sequences,” Archiv der Mathematik, vol. 81, no. 1, pp. 82-89, 2003. · Zbl 1041.40001 This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.