Introduction to Fuzzy Systems

Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 288)

Abstract

Fuzzy logic since its conception in 1965 [11] has been used in various areas of science, economics, manufacturing, medicine etc [1, 2, 3, 4, 7, 8, 9]. It constitutes, along with other methods such as neural networks or evolutionary algorithms, the idea of soft computing [5]. Fuzzy sets used in fuzzy rules can be a tool to model linguistic values like “small” or “high” [12]. This chapter presents basic definitions of fuzzy logic and fuzzy systems based on [10].

Keywords

Membership Function Fuzzy System Fuzzy Rule Inference Rule Fuzzy Inference System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bezdek, J., Keller, J., Krisnapuram, R., Pal, N.: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing. Kluwer Academic Press (1999)Google Scholar
  2. 2.
    Bezdek, J.C.: Fuzzy Models for Pattern Recognition. IEEE Press, New York (1992)Google Scholar
  3. 3.
    Czogała, E., Łęski, J.: Fuzzy and Neuro-Fuzzy Intelligent Systems. Springer, New York (2000)MATHCrossRefGoogle Scholar
  4. 4.
    Dubois, D., Prade, H.: Fuzzy sets and systems - Theory and applications. Academic press, New York (1980)MATHGoogle Scholar
  5. 5.
    Jang, R.J.S., Sun, C.T., Mizutani, E.: Neuro-Fuzzy and Soft Computing, A Computational Approach to Learning and Machine Intelligence. Prentice-Hall, Upper Saddle River (1997)Google Scholar
  6. 6.
    Kuncheva, L.: Combining Pattern Classifiers. STUDFUZZ. John Wiley & Sons (2004)Google Scholar
  7. 7.
    Nauck, D.: Foundations of Neuro-Fuzzy Systems. John Wiley, Chichester (1997)Google Scholar
  8. 8.
    Pedrycz, W.: Fuzzy Control and Fuzzy Systems. Research Studies Press, London (1989)MATHGoogle Scholar
  9. 9.
    Rutkowski, L.: Flexible Neuro-Fuzzy Systems. Kluwer Academic Publishers (2004)Google Scholar
  10. 10.
    Rutkowski, L.: Computational Intelligence Methods and Techniques. Springer, Heidelberg (2008)MATHGoogle Scholar
  11. 11.
    Zadeh, L.A.: Fuzzy sets. Information Control 8, 338–353 (1965)MathSciNetMATHCrossRefGoogle Scholar
  12. 12.
    Zadeh, L.A.: The concept of a linguistic variable and its application to approximate reasoning. Inf. Sci. 8(3), 199–249 (1975)MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Department of Computer EngineeringCzestochowa University of TechnologyCzestochowaPoland

Personalised recommendations