title: Understanding Neural Networks and Fuzzy Logic: Basic Concepts and Applications
author:  Stamatios V. Kartalopoulos 
description: Electrical Engineering Understanding Neural Networks and FuzzyLogic Basic Concepts and Applications Stamatios v. Kartalopoulos,PhD, AT&amp;T Bell Laboratories A Volume in the IEEE PressUnderstanding Science &amp; Technology Series Understand thefundamentals of the emerging field of fuzzy neural networks, theirapplications and the most used paradigms with thiscarefully-organized state-of-the-art textbook. Previously tested ata number of noteworthy conference tutorials, the simple numericalexamples presented in this book act as an excellent tool forprogressive learning. Topics covered include:<ul type="square"><li>Biological neural networks</li><li>Fuzzy logic</li><li>Artificial neural networks</li><li>Neural network paradigms</li><li>Artificial neuron modeling</li><li>Fuzzy neural networks</li><li>Applications, and more!</li></ul>Understanding Neural Networks and Fuzzy Logic offers a simplepresentation and bottom-up approach that is ideal for workingprofessional engineers, undergraduates, medical/biology majors, andanyone with a nonspecialist background. Also of interest from IEEEPress&#133; Industrial Applications of Fuzzy Control andIntelligent Systems Edited by Drs. John Yen and Reza Langari, TexasA &amp; M University, and Dr. Lotfi A. Zadeh, University ofCalifornia at Berkeley 1995 / Hardcover / 350 pp / IEEE Order No.PC4002 / ISBN 0-7803-1048-9 Fuzzy Models for Pattern RecognitionMethods That Search for Structures in Data Edited by James C.Bezdek, University of West Florida, and Sankar K. Pal, IndianStatistical Institute, Calcutta 1992 / Softcover / 552 pp / IEEEOrder No. PC3178 / ISBN 0-7803-0422-5 About the series&#133; TheIEEE Press Understanding Science &amp; Technology Series treatsimportant topics in science and technology in a simple andeasy-to-understand manner. Designed expressly for the nonspecialistengineer, scientist, or technician, as well as the technologicallycurious, each volume stresses practical information overmathematical theorems and complicated derivations.
zlib_text: We are surprisingly flexible in processing infonnation in the real world.
  The human brain, consisting of 1011 neurons, realizes intelligent infonna-
  tion processing based on exact and common sense reasoning. Scientists
  have been trying to implement human intelligence in computers in various 
  ways. Artificial intelligence (AI) pursues exact logical reasoning based
  on symbol manipulation. Fuzzy engineering uses analog values to realize
  fuzzy but robust and efficient reasoning. They are macroscopic ways to
  realize human intelligence at the level of symbols and rules. Neural networks 
  are a microscopic approach to the intelligence of the brain in which
  information is represented by excitation patterns of neurons.
  All of these approach es are partially successful in implementing human
  intelligence, but are still far from the real one. AI uses mathematically
  rigorous logical reasoning but is not flexible and is difficult to implement.
  Fuzzy systems provide convenient and flexible methods of 