Objective


  • I am completing a thesis in machine learning / systems control algorithms. 


    





    Time
    

  • week of June 19 - connect with thesis advisor, receive 2 of his research papers on FLC 

  • week of June 24 - begin Phase 1:  Survey Fuzzy Logic body of knowledge

  • week of July 01 - Complete review of Chapter One, Fuzzy Logic ..." Bojadziev 2007;  order 2 FL books from Amazon 

  • week of July 09 - Complete review of 50 background research papers;  receive 2 FL books from Amazon 

  • week of July 16 - Complete review of previous mathematical methods research

  • week of July 23 - Complete review of Chapters 1-9, Essentials of Fuzzy Modeling and Control

  • week of July 30 - Complete review of Chapters 11-16, Fuzzy Systems Theory and Applications

  • week of Aug 06 - Complete review of Chapters 06-10, Fuzzy Systems Theory and Applications

  • week of Aug 13 - Complete review of Chapters 01-05, Fuzzy Systems Theory and Applications

  • week of Aug 13 - begin Phase 2:  Hone thesis topic

  • week of Aug 20 - review trade automation industry development

  • week of Aug 27 - Build a Matlab systems control workbench


    


    References
    

  •  Fuzzy Systems Theory and Its Applications, Terano, Asai, Sugeno, 1992

  •  Essentials of Fuzzy Modeling and Control, Yager, 1994

  • online resources - see soft computing blog


    


    Questions 
    

  • Q:  Does NN assimilate FL ?  A: No, NN complements FL. The 3 principal constituents of soft computing are: Fuzzy Logic (FL), Neural Networks (NN), and Probablistic Reasoning (PR)

  • Principle of the excluded middle does *not* hold in FL - how can that be illustrated ...

  • Principle of incompatibility - precision and complexity are mutually exclusive.  Can this be measured in the lab, like the Heisenberg Uncertainty principle.  

  • Taking it one step further, there should be a fundamental constant analogous to Plank's constant.   What are the dimensions of this constant. What kind of experiment can determine the value. 


    


    Discussion, Feedback
    

  • see Blog


    


    C++ STL algorithm development
    

  •  Generic Template fuzzy logic class library 


    
 

    ECE 560 Fuzzy Logic course outline - one comparable
    

  • 1. Crisp sets 

  • 2. Fuzzy sets, operations with fuzzy sets, membership functions, fuzzification 

  • 3. Fuzzy relations and solution of relational equations 

  • 4. Approximate reasoning 

  • 5. Fuzzy rules 

  • 6. Fuzzy models and programming 

  • 7. Applications to areas such as control, expert systems, pattern recognition, information fusion 


    


    $
    

  • $15  Amazon book 

  • $25  Amazon book 

  • $40  ACM digital library

  • $300 Matlab version upgrade 


    



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