Multivariate contraction mapping principle in Menger probabilistic metric spaces

The Journal of Nonlinear Sciences and its Applications

YongchunXu¹  YanxiaTang¹  JinyuGuan¹  YongfuSu² 

[1] Department of Mathematics, College of Science, Hebei North University, Zhangjiakou 075000, China;Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, China

关键词: Contraction mapping principle;    probabilistic metric spaces;    product spaces;    multivariate fixed point.;   

DOI  :  10.22436/jnsa.010.09.17

学科分类：社会科学、人文和艺术（综合）

来源: Shomal University

【 摘 要 】

The purpose of this paper is to prove the multivariate contraction mapping principle of \(N\)-variables mappings in Menger probabilistic metric spaces. In order to get the multivariate contraction mapping principle,the product spaces of Menger probabilistic metric spaces are subtly defined which is used as an important method for the expected results. Meanwhile, the relative iterative algorithm of the multivariate fixed point is established. The results of this paper improve and extend the contraction mapping principle ofsingle variable mappings in the probabilistic metric spaces.

【 授权许可】

Unknown