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Fuzzy Logic: Intelligence, Control, and Information By John Yen, Reza Langari

Free PDF Fuzzy Logic: Intelligence, Control, and Information By John Yen, Reza Langari

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Sales Rank: #1165408 in Books
Published on: 1998-11-23
Original language: English
Number of items: 1
Dimensions: 9.00" h x 1.30" w x 7.40" l, 2.24 pounds
Binding: Paperback
548 pages

Review
``Superb. This one-word assessment summarizes my view of "Fuzzy Logic: Intelligence, Control and Information," (or FL:ICI for short) -- a long-awaited text by Professors John Yen and Reza Langari. Written with authority and high expository skill, FL: ICI reflects the extensive experience of its authors in both teaching and research in fuzzy logic and related fields. ... The historical notes, the bibliographies and the exercises contribute substantially to the reader-friendliness of FL:ICI and enhance its value as a text.

In sum, FL:ICI is in every respect an outstanding contribution to the literature of fuzzy logic and soft computing, and is a must for anyone who is interested in the conception, design and utilization of information/intelligent/control systems. Professors Yen and Langari deserve our thanks and congratulations.'' -- Lotfi A. Zadeh, Professor, University of California, Berkeley

From the Back Cover

Providing equal emphasis on theoretical foundations and practical issues, this book features fuzzy logic concepts and techniques in intelligent systems, control, and information technology.

FEATURES

Comprehensive and up-to-date coverage.
Provides examples and exercises that are related to real world problems.
Uses Fuzzy Logic Toolbox for MATLAB™ to demonstrate exemplar applications and to develop hands-on exercises.
Provides design guidelines and design methods for developing fuzzy logic applications.
Provides a modern perspective of the fuzzy logic technology.
Introduces core concepts and techniques gently in two steps.
Provides relevant background materials that encompass a wide range of disciplines.
Introduces the connection between fuzzy logic and related ideas, methods, and theories developed in other disciplines (e.g., artificial intelligence, probability theory, control, model identification, etc.).
Summarizes key concepts at the end of each chapter.
Highlights motivations and benefits of employing fuzzy logic in control engineering and information systems.
Discussion of open research issues and their implications.
A chapter is devoted to the subject of "How to design a fuzzy system." In addition, several other chapters (e.g., the chapters on fuzzy model identification and neuro-fuzzy systems) introduce techniques for automating decisions in the design process using training data (i.e., examples) and learning algorithms.
Advanced topics are separated from the basic material in the chapter that immediately follows.

About the Author
ROBERT L. POPP, PhD, is currently an Executive Vice President of Aptima, Inc., and formerly a senior executive within the Defense Department, serving in the Office of the Secretary of Defense and Defense Advanced Research Projects Agency (DARPA). He is an expert in national security and counter-terrorism, authoring numerous scientific papers and providing many technical briefings and interviews on the subject. He is a member of the Defense Science Board (DSB), Senior Associate for the Center for Strategic and International Studies (CSIS), Senior Member of the IEEE, member of ACM and AAAS, founding Fellow of the University of Connecticut Academy of Distinguished Engineers, and a lifetime member of HOG (the Harley Owners Group).

JOHN YEN, PhD, is currently University Professor of Information Sciences and Technology and Professor in Charge, College of Information Sciences and Technology at The Pennsylvania State University. He is the author of numerous papers, holds one patent, chairs IEEE FIPA standard working groups on human agent communications, and is a member and Fellow of IEEE.

Langari-Texas A&M University

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