Book review: Fuzzy Engineering by Bart Kosko (Prentice Hall, 1997)

ABSTRACT

Practical Application": That should be the goal of all theory and technology development. This review offers opinions written from that perspective. The review started with the question, "Can this book be used as a guide to implementing a new technology by someone with related knowledge?" Generally, the reader will find a very useful book with application insights and extensions to the author's previous developments. Each chapter gives concept, theory, and application. However, except for expert peers in fuzzy engineering, statistics, and communications engineering, it does not explain the applications in sufficient detail to give a clear path to implementation. The concepts discussed in this book are part of the more general data mining technology.

REFERENCES

• 1: Bart Kosko, Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence, Prentice-Hall, Inc., Upper Saddle River, NJ, 1992
• 2: Kosko, Bart, 1993. <i>Fuzzy Thinking: The New Science of Fuzzy Logic.</i> New York, NY:Hyperion.
• 3: Meystel, Alexander, M. 1996. <i>Intelligent Systems: A Semiotic Perspective.</i> International Journal of Intelligent Control and Systems, Vol. 1, No. 1, pp 31--57.
• 4: Meystel, Alex. 1995. <i>Semiotic Modeling and Situation Analysis: An Introduction.</i> Bala Cynwyd, PA: AdRem.
• 5: Ross, Timothy, J. 1994. <i>Fuzzy Logic with Engineering Applications.</i> New York, NY: McGraw-Hill.
• 6: Jamshidi, Mohammad; Ross, Timothy; Vadiee, Nader; Jun 93. <i>Hands-on Fuzzy Logic.</i> Course Notes, University of Mexico/College of Engineering.
• 7: Teuvo Kohonen , T. Kohonen , M. R. Schroeder , T. S. Huang, Self-Organizing Maps, Springer-Verlag New York, Inc., Secaucus, NJ, 2001
• 8: Post, Emil, L. 1921. <i>Introduction to a General Theory of Elementary Propositions.</i> American Journal of Mathematics, V. 43, pp. 163--185.
• 9: Zadeh, Lofti, A. 1973. <i>Outline of a New Approach to the Analysis of Complex Systems and Decision Processes.</i> IEEE Transactions on Systems, Man, and Cybernetics, V. SMC-3, No. 1, pp. 28--44 (January).
• 10: Hongjun Lu , Rudy Setiono , Huan Liu, NeuroRule: A Connectionist Approach to Data Mining, Proceedings of the 21th International Conference on Very Large Data Bases, p.478-489, September 11-15, 1995
• 11: Hongjun Lu , Rudy Setiono , Huan Liu, Effective Data Mining Using Neural Networks, IEEE Transactions on Knowledge and Data Engineering, v.8 n.6, p.957-961, December 1996 [doi>10.1109/69.553163]
• 12: Rudy Setiono , Huan Liu, Symbolic Representation of Neural Networks, Computer, v.29 n.3, p.71-77, March 1996 [doi>10.1109/2.485895]
• 13: Khan, Emadur, R. 1996. <i>Fuzzy Logic Design Generator Using a Neural Network to Generate Fuzzy Logic Rules and Membership Functions for Use in Intelligent Systems.</i> US Patent 5,579,439 (November).
• 14: Stephen I. Gallant, Neural network learning and expert systems, MIT Press, Cambridge, MA, 1993
• 15: Buhusi, Catalin V. 1993. <i>Neural learning in automatic fuzzy systems synthesis.</i> Proceedings of the International Joint Conference on Neural Networks, V. 1, pp. 786--789.
• 16: McMillan, Clayton; Mozer, Michael C.; Smolensky, Paul. 1991. <i>Learning explicit rules in a neural network.</i> Proceedings of the International Joint Conference on Neural Networks, V. 2, pp. 83--88.
• 17: Klimasauskas, Casey, 1990. <i>Neural Computing.</i> Pittsburgh, PA: NeuralWare.
• 18: Lippmann, R. 1987. <i>An Introduction to Computing With Neural Nets.</i> IEEE ASSP Magazine, pp. 4--22 (April).