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Table of contents (6 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Several themes run through this book. The first is the theory of triangular norms (t-norms), which is closely related to fixed point theory in probabilistic metric spaces. Its recent development has had a strong influence upon the fixed point theory in probabilistic metric spaces.
In Chapter 1 some basic properties of t-norms are presented and several special classes of t-norms are investigated. Chapter 2 is an overview of some basic definitions and examples from the theory of probabilistic metric spaces. Chapters 3, 4, and 5 deal with some single-valued and multi-valued probabilistic versions of the Banach contraction principle. In Chapter 6, some basic results in locally convex topological vector spaces are used and applied to fixed point theory in vector spaces.
Audience: The book will be of value to graduate students, researchers, and applied mathematicians working in nonlinear analysis and probabilistic metric spaces.
Authors and Affiliations
Bibliographic Information
Book Title: Fixed Point Theory in Probabilistic Metric Spaces
Authors: Olga Hadžić, Endre Pap
Series Title: Mathematics and Its Applications
DOI: https://doi.org/10.1007/978-94-017-1560-7
Publisher: Springer Dordrecht
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 2001
Hardcover ISBN: 978-1-4020-0129-1Published: 30 November 2001
Softcover ISBN: 978-90-481-5875-1Published: 08 December 2010
eBook ISBN: 978-94-017-1560-7Published: 29 June 2013
Edition Number: 1
Number of Pages: IX, 273
Topics: Operator Theory, Probability Theory and Stochastic Processes, Functional Analysis, Topology, Mathematical Logic and Foundations