CMU Artificial Intelligence Repository
 
   
   
   
   
  
FuNeGen: Fuzzy neural system
areas/fuzzy/systems/funegen/
FuNeGen is a fuzzy neural system capable of generating fuzzy
classification systems (as C-code) from sample data. This directory
contains a demonstration version of FuNeGen.
Origin:   
   obelix.microelectronic.e-technik.th-darmstadt.de:/pub/neurofuzzy/
Version:      1.0 (5-JUL-94)
Requires:     IBM PC (286 or higher)
CD-ROM:       Prime Time Freeware for AI, Issue 1-1
Contact:      Saman K. Halgamuge
              Darmstadt University of Technology
              Institute of Microelectronic Systems
              Karlstr. 15
              D-64283 Darmstadt
              Germany
              
              Tel: ++49 6151 16-5136
              Fax: ++49 6151 16-4936
              Email: 
Keywords:
   Authors!Halgamuge, FuNeGen, Fuzzy Logic, Neural Networks
References:
   [1] E. Anderson, "The Irises of the Gaspe Peninsula", Bull.~Amer.~Iris
       Soc. 59, 1935.
   
   [2] S. K. Halgamuge and M. Glesner, "A Fuzzy-Neural Approach for
       Pattern Classification with the Generation of Rules based on
       Supervised Learning", Neuro-Nimes 92, Nimes, France, November 1992.
   
   [3] S. K. Halgamuge and M. Glesner, "Neural Networks in Designing
       Fuzzy Systems for Real World Applications", International Journal for
       Fuzzy Sets and Systems, H.-J. Zimmermann, editor, North Holland, 1994.
   
   [4] S. K. Halgamuge, W. Poechmueller, and M. Glesner, "A Rule based
       Prototype System for Automatic Classification in Industrial Quality
       Control", IEEE International Conference on Neural Networks 93, San
       Francisco, USA, March 1993.
   
   [5] S. K. Halgamuge, H.-J. Herpel, and M. Glesner, "An Automotive
       Application With Neural Network Based Knowledge Extraction",
       Mechatronical Computer Systems for Perception and Action 93, Halmstad,
       Sweden, June 1993.
   
   [6] S. K. Halgamuge and M. Glesner, "The Fuzzy Neural Controller FuNe
       II with a New Adaptive Defuzzification Strategy Based on CBAD
       Distributions", European Congress on Fuzzy and Intelligent
       Technologies 93, Aachen, Germany, September 1993.
   
   [7] S. K. Halgamuge, W. Poechmueller, A. Pfeffermann, P.
       Schweikert, and M. Glesner, "A New Method for Generating Fuzzy
       Classification Systems Using RBF Neurons with Extended RCE Learning",
       IEEE International Conference on Neural Networks 94, Orlando, USA,
       June 1994.
   
   [8] S. K. Halgamuge, T. Wagner, and M. Glesner, "Validation and
       Application of an adaptive transparent Defuzzification Strategy for
       Fuzzy Control", IEEE International Conference on Fuzzy Systems 94,
       Orlando, USA, June 1994.
   
   [9] S. K. Halgamuge, "Advanced Methods for Fusion of Fuzzy Systems and 
       Neural Networks in Intelligent Data Processing", PhD thesis, Darmstadt
       University of Technology, Department of Computer Engineering, 1994.
   
   [10] S. K. Halgamuge, W. Poechmueller, and M. Glesner, "An
        Alternative Approach for Generation of Membership Functions and Fuzzy
        Rules Based on Radial and Cubic Basis Function Networks", Technical
        Report, Darmstadt University of Technology, Department of Computer
        Engineering, Institute of Microelectronic Systems, 1994.
Last Web update on Mon Feb 13 10:22:17 1995 
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