SVD-based complexity reduction of "near PSGS" fuzzy systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

With the help of the SVD-based (Singular Value Decomposition) complexity reduction method, not only the redundancy of fuzzy rule-bases can be eliminated, but also further, non-exact reduction can be made, considering the allowable error. Namely, in case of higher allowable error, the result may be a less complex fuzzy inference system, with a smaller rule-base. This property of the SVD-based reduction method makes possible the usage of fuzzy systems in time-critical applications and makes possible the combining of fuzzy systems with anytime techniques to cope with the changing circumstances during the operation of the system. However, while the SVD-based reduction can be applied to PSGS fuzzy systems, in case of rule-bases, constructed from expert knowledge, the input fuzzy sets are not always in Ruspinipartition. This paper extends the SVD-based reduction to "near PSGS" fuzzy systems, where the input fuzzy sets are not in Ruspini-partition.

Original languageEnglish
Title of host publication2003 IEEE International Symposium on Intelligent Signal Processing
Subtitle of host publicationFrom Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-36
Number of pages6
ISBN (Electronic)0780378644, 9780780378643
DOIs
Publication statusPublished - Jan 1 2003
Event3rd IEEE International Symposium on Intelligent Signal Processing, WISP 2003 - Budapest, Hungary
Duration: Sep 6 2003 → …

Publication series

Name2003 IEEE International Symposium on Intelligent Signal Processing: From Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings

Other

Other3rd IEEE International Symposium on Intelligent Signal Processing, WISP 2003
CountryHungary
CityBudapest
Period9/6/03 → …

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Keywords

  • Anytime systems
  • Complexity reduction
  • Fuzzy systems

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Mathematics(all)
  • Software
  • Computer Science Applications

Cite this

Takács, O., & Várkonyi-Kóczy, A. R. (2003). SVD-based complexity reduction of "near PSGS" fuzzy systems. In 2003 IEEE International Symposium on Intelligent Signal Processing: From Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings (pp. 31-36). [1275809] (2003 IEEE International Symposium on Intelligent Signal Processing: From Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISP.2003.1275809