Applicability of fuzzy flip-flops in the implementation of neural networks

Rita Lovassy, László T. Kóczy, László Gál

Research output: Paper

7 Citations (Scopus)

Abstract

The concept of various type fuzzy flip-flops (F3) has already been proposed. We have done some investigations on a large scope of F 3s based on different t-norms and conorms. Also we have shown that a few F3 types are suitable for realizing neurons in multilayer perceptrons. The aim of this paper is to present a comparison of the performance of several type neural networks based on fuzzy J-K and also fuzzy D flip-flops (the latter derived from the former type). The behavior of algebraic, Yager, Dombi and Hamacher type fuzzy flip-flop neural networks are presented. The best fitting t-norm and corresponding fuzzy flip-flop type will be presented in terms of function approximation capability.

Original languageEnglish
Pages333-344
Number of pages12
Publication statusPublished - dec. 1 2008
Event9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2008 - Budapest, Hungary
Duration: nov. 6 2008nov. 8 2008

Other

Other9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2008
CountryHungary
CityBudapest
Period11/6/0811/8/08

ASJC Scopus subject areas

  • Artificial Intelligence
  • Information Systems

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    Lovassy, R., Kóczy, L. T., & Gál, L. (2008). Applicability of fuzzy flip-flops in the implementation of neural networks. 333-344. Paper presented at 9th International Symposium of Hungarian Researchers on Computational Intelligence and Informatics, CINTI 2008, Budapest, Hungary.