Non exact complexity reduction of generalized neuro-fuzzy networks

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

1 Citation (Scopus)

Abstract

In modern measurement, control, monitoring and fault diagnosis systems, there is an increasing need for the use of non-classical computing methods. On the other hand, in these systems the available time and resources are usually limited, so methods with lower computational complexity are needed. Thus, the need arises to have formal methods for the complexity reduction of different soft-computing techniques. This paper discusses a possible method for the non-exact reduction of generalized type neuro-fuzzy systems, and gives the necessary error-bounds of the reduction.

Original languageEnglish
Title of host publicationIEEE International Conference on Fuzzy Systems
Pages980-983
Number of pages4
Volume2
Publication statusPublished - 2001
Event10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia
Duration: Dec 2 2001Dec 5 2001

Other

Other10th IEEE International Conference on Fuzzy Systems
CountryAustralia
CityMelbourne
Period12/2/0112/5/01

Fingerprint

Soft computing
Formal methods
Fuzzy systems
Failure analysis
Computational complexity
Monitoring

ASJC Scopus subject areas

  • Software
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

Takács, O., Várkonyi-Kóczy, A., & Várlaki, P. (2001). Non exact complexity reduction of generalized neuro-fuzzy networks. In IEEE International Conference on Fuzzy Systems (Vol. 2, pp. 980-983)

Non exact complexity reduction of generalized neuro-fuzzy networks. / Takács, Orsolya; Várkonyi-Kóczy, A.; Várlaki, P.

IEEE International Conference on Fuzzy Systems. Vol. 2 2001. p. 980-983.

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

Takács, O, Várkonyi-Kóczy, A & Várlaki, P 2001, Non exact complexity reduction of generalized neuro-fuzzy networks. in IEEE International Conference on Fuzzy Systems. vol. 2, pp. 980-983, 10th IEEE International Conference on Fuzzy Systems, Melbourne, Australia, 12/2/01.
Takács O, Várkonyi-Kóczy A, Várlaki P. Non exact complexity reduction of generalized neuro-fuzzy networks. In IEEE International Conference on Fuzzy Systems. Vol. 2. 2001. p. 980-983
Takács, Orsolya ; Várkonyi-Kóczy, A. ; Várlaki, P. / Non exact complexity reduction of generalized neuro-fuzzy networks. IEEE International Conference on Fuzzy Systems. Vol. 2 2001. pp. 980-983
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