Cascaded centralized TSK fuzzy system: Universal approximator and high interpretation

Shitong Wang, Fu Lai Korris Chung, Shen HongBin, Hu Dewen

Research output: Journal article publicationJournal articleAcademic researchpeer-review

30 Citations (Scopus)


When applying fuzzy systems for data analysis, their approximation and interpretation capabilities are two important aspects. Cascaded fuzzy system (CFS) is a new special class of hierarchical fuzzy systems in architectures proposed by Duan and Chung [IEEE Trans. Fuzzy Syst. 9 (2) (2001) 293] but its universal approximation capability is still not proved. When CFS is utilized in fuzzy data analysis/modeling, it seems very difficult to give a reasonable interpretation for intermediate variables and the corresponding fuzzy rules. A new cascaded centralized TSK fuzzy system (CCTSKFS) is presented in this paper, whose universal approximation capability is proved in detail, and what's more, we can interpret CCTSKFS more rationally. Finally, our experimental results demonstrate that CCTSKFS outperforms the classical cascaded TSK fuzzy system (CTSKFS) in approximation capability and robustness.
Original languageEnglish
Pages (from-to)131-145
Number of pages15
JournalApplied Soft Computing Journal
Issue number2
Publication statusPublished - 1 Jan 2005


  • Fuzzy system
  • Interpretation
  • Universal approximation

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Artificial Intelligence


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