Probabilistic metric spaces

By:

Schweitzer, B

Contributor(s):

Sklar, A. Co author

Material type: Text

TextPublication details: New York Dover Publications 2005Description: vi, 314p. With indexISBN:

9780486445144

Subject(s):

DDC classification:

514.32 S2P7

Summary: This distinctly non classical treatment focuses on developing aspects that differ from the theory of ordinary metric spaces, working directly with probability distribution functions rather than random variables. The two-part treatment begins with an overview that discusses the theory's historical evolution, followed by a development of related mathematical machinery. The presentation defines all needed concepts, states all necessary results, and provides relevant proofs. The second part opens with definitions of probabilistic metric spaces and proceeds to examinations of special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. Throughout, the authors focus on developing aspects that differ from the theory of ordinary metric spaces, rather than simply transferring known metric space results to a more general setting. http://store.doverpublications.com/0486445143.html

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode	Item holds
Book	Ahmedabad General Stacks	Non-fiction	514.32 S2P7 (Browse shelf(Opens below))	Available		198926

Total holds: 0

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Previous	514 S4I6 Introduction to topology	514 Z6T6 Topology for computing	514.23 K2C6 Computational homology	514.32 S2P7 Probabilistic metric spaces	514.72 M4T6 Topology from the differentiable viewpoint	514.742 F3C4 Chaos and dynamical systems	515 A2 Acta numerica Volume 1 1992	Next

This distinctly non classical treatment focuses on developing aspects that differ from the theory of ordinary metric spaces, working directly with probability distribution functions rather than random variables. The two-part treatment begins with an overview that discusses the theory's historical evolution, followed by a development of related mathematical machinery. The presentation defines all needed concepts, states all necessary results, and provides relevant proofs.
The second part opens with definitions of probabilistic metric spaces and proceeds to examinations of special classes of probabilistic metric spaces, topologies, and several related structures, such as probabilistic normed and inner-product spaces. Throughout, the authors focus on developing aspects that differ from the theory of ordinary metric spaces, rather than simply transferring known metric space results to a more general setting.

http://store.doverpublications.com/0486445143.html

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