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2008 | Vol. 56, nr 1 | 71-76
Tytuł artykułu

Linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system

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Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper presents Gupta's relational decomposition technique expanded on linguistic level. It allows to reduce the hardware cost of the fuzzy system or the computing time of the final result, especially when referring to First Aggregation Then Inference (FATI) relational systems or First Inference Then Aggregation (FITA) rule systems. The inference result of the hierarchical system using decomposition technique is more fuzzy than of the classical system. The paper describes a linguistic decomposition technique based on partitioning the knowledge base of the fuzzy inference system. It allows to decrease or even totally remove a redundant fuzziness of the inference result.
Wydawca

Rocznik
Strony
71-76
Opis fizyczny
Bibliogr. 14 poz., rys., tab.
Twórcy
autor
  • Institute of Electronics, Silesian University of Technology 16 Akademicka St., 44-100 Gliwice, Poland, Bernard.wyrwol@polsl.pl
Bibliografia
  • [1] E. Czogała and W. Pedrycz, Elements and Methods of Fuzzy Set Theory, PWN, Polish Scientific Publishers, Warsaw, 1985.
  • [2] D. Rutkowska, M. Pilinski, and L. Rutkowski, Neural Networks, Genetic Algorithms and Fuzzy Systems, PWN, Polish Scientific Publishers, Warsaw, 1997.
  • [3] D. Driankov, H. Hellendoorn, and M. Reinfrank, "An introduction to Fuzzy Control", WNT, Warszawa, 1996.
  • [4] R.R. Yager and D.P. Filev, Principles of Modeling and Fuzzy Control, WNT, Warszawa, 1995, (in Polish).
  • [5] M.M. Gupta, J.B. Kiszka, and G.M. Trojan, "Multivariable structure of fuzzy control systems", IEEE Transactions on Systems, Man, and Cybernetics 16 (5), 638-656 (1986).
  • [6] P.G. Lee, K. Lee Kyun, and G.J. Jeon, "An index of applicability for the decomposition method of multivariable fuzzy systems", IEEE Transactions on Fuzzy Systems 3 (3), 364-369 (1995).
  • [7] B. Wyrwoł, Hardware Realisation of Approximate Inference with the Use of Programmable Logic Systems, PhD Thesis, Silesian University of Technology, Gliwice, 2004.
  • [8] B. Wyrwoł "The rule-relation system of approximate inference", IV State Conf. on Electronics 2, 475-480 (2005).
  • [9] I. Baturone, S. Sanchez-Solano, A. Barriga, and J.L. Huertas, "Implementation of CMOS fuzzy controllers as mixed-signal integrated circuits", IEEE Transactions on Fuzzy Systems 5, 1-19 (1997).
  • [10] D. Kim and In-Hyun Cho, "An accurate and cost-effective COG defuzzifier without the multiplier and the divider", Fuzzy Sets and Systems 104, 229-244 (1999).
  • [11] A. Ollero and A.J. Garcia-Cerezo, "Direct digital control, autotuning and supervision using fuzzy logic", Fuzzy Sets and Systems 30, 135-153 (1989).
  • [12] T. Yamakawa, "Stabilization of an inverted pendulum by a high-speed fuzzy logic controller hardware system", Fuzzy Sets and Systems 32, 161-180 (1989).
  • [13] H.D. Hurdon, Fuzzy Logic Fan Controller, ntia.its. bldrdoc.gov/pub/fuzzy (1993).
  • [14] R. Rovatti, R. Guerrieri, and G. Baccarani, "An enhanced two-level Boolean synthesis methodology for fuzzy rules minimization", IEEE Trans. on Fuzzy Systems 3, 288-299 (1995).
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG5-0031-0011
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