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Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Common Fixed Point Theorems in Menger Probabilistic Quasimetric Spaces | Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2009 Article ID 546273 11 pages doi 10.1155 2009 546273 Research Article Common Fixed Point Theorems in Menger Probabilistic Quasimetric Spaces Shaban Sedghi 1 Tatjana Zikic-Dosenovic 2 and Nabi Shobe3 1 Department of Mathematics Islamic Azad University-Babol Branch P.O. Box 163 Ghaemshahr Iran 2 Faculty of Technology University of Novi Sad Bulevar Cara Lazara 1 21000 Novi Sad Serbia 3 Department of Mathematics Islamic Azad University-Babol Branch Babol Iran Correspondence should be addressed to Shaban Sedghi sedghLgh@yahoo.com Received 21 November 2008 Accepted 19 April 2009 Recommended by Massimo Furi We consider complete Menger probabilistic quasimetric space and prove common fixed point theorems for weakly compatible maps in this space. Copyright 2009 Shaban Sedghi et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. 1. Introduction and Preliminaries K. Menger introduced the notion of a probabilistic metric space in 1942 and since then the theory of probabilistic metric spaces has developed in many directions 1 . The idea of K. Menger was to use distribution functions instead of nonnegative real numbers as values of the metric. The notion of a probabilistic metric space corresponds to the situations when we do not know exactly the distance between two points we know only probabilities of possible values of this distance. Such a probabilistic generalization of metric spaces appears to be well adapted for the investigation of physiological thresholds and physical quantities particularly in connections with both string and E-infinity theory see 2-5 . It is also of fundamental importance in probabilistic functional analysis nonlinear analysis and applications 6-10 . In the sequel we will adopt usual terminology notation and .