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Fuzzy Sets, Uncertainty And Information/ George J. Klir, Tina A. Fegler

By: Contributor(s): Material type: TextTextPublication details: New Delhi: PHI Learning Private Limited, 2010.Edition: Eastern Economy EditionDescription: 355 pISBN:
  • 9788120306950
  • 9780133459845
Subject(s): DDC classification:
  • 006.3  KLI
Summary: The concept of uncertainty and its relationship tothe increasingly important concept of information and complexity need to be brought under a newmathematical formulation. This book is intended to make an understanding of this mathematical formalism accessible to students and professionals ina broad range of disciplines and covers the variousissues of uncertainty, information and complexityfrom a broad perspective based on formalism of fuzzyset theory. No prior knowledge of fuzzy set theory orinformation theory is required; the reader is howeverassumed to be familiar with basic notions of settheory, logic and probability theory, though thefundamentals of these subject areas are brieflyoverviewed in the book.The book is suitable as a text at the advanced undergraduate/postgraduate level that covers uncertainty, information and complexity from a broadperspective in mathematics courses in artificialintelligence, engineering and computer science.
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Holdings
Item type Current library Home library Collection Call number Status Date due Barcode
Book Book Dept. of Futures Studies Processing Center Dept. of Futures Studies Knowledge Management 006.3 KLI (Browse shelf(Opens below)) Available DFSKM30

The concept of uncertainty and its relationship tothe increasingly important concept of information and complexity need to be brought under a newmathematical formulation. This book is intended to make an understanding of this mathematical formalism accessible to students and professionals ina broad range of disciplines and covers the variousissues of uncertainty, information and complexityfrom a broad perspective based on formalism of fuzzyset theory. No prior knowledge of fuzzy set theory orinformation theory is required; the reader is howeverassumed to be familiar with basic notions of settheory, logic and probability theory, though thefundamentals of these subject areas are brieflyoverviewed in the book.The book is suitable as a text at the advanced undergraduate/postgraduate level that covers uncertainty, information and complexity from a broadperspective in mathematics courses in artificialintelligence, engineering and computer science.

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