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

Orsolya Takács, A. Várkonyi-Kóczy

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: From Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-36
Number of pages6
ISBN (Print)0780378644, 9780780378643
DOIs
Publication statusPublished - 2003
Event3rd IEEE International Symposium on Intelligent Signal Processing, WISP 2003 - Budapest, Hungary
Duration: Sep 6 2003 → …

Other

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

Fingerprint

Fuzzy systems
Singular value decomposition
Fuzzy Systems
Rule Base
Reduction Method
Fuzzy Sets
Fuzzy sets
Fuzzy Rule Base
Fuzzy Inference System
Redundancy
Fuzzy inference
Fuzzy rules
Partition

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. (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] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISP.2003.1275809

SVD-based complexity reduction of "near PSGS" fuzzy systems. / Takács, Orsolya; Várkonyi-Kóczy, A.

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., 2003. p. 31-36 1275809.

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

Takács, O & Várkonyi-Kóczy, A 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., 1275809, Institute of Electrical and Electronics Engineers Inc., pp. 31-36, 3rd IEEE International Symposium on Intelligent Signal Processing, WISP 2003, Budapest, Hungary, 9/6/03. https://doi.org/10.1109/ISP.2003.1275809
Takács O, Várkonyi-Kóczy A. 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. Institute of Electrical and Electronics Engineers Inc. 2003. p. 31-36. 1275809 https://doi.org/10.1109/ISP.2003.1275809
Takács, Orsolya ; Várkonyi-Kóczy, A. / SVD-based complexity reduction of "near PSGS" fuzzy systems. 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., 2003. pp. 31-36
@inproceedings{c21046e0fef840a79eda3bc43b827fb8,
title = "SVD-based complexity reduction of {"}near PSGS{"} fuzzy systems",
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.",
keywords = "Anytime systems, Complexity reduction, Fuzzy systems",
author = "Orsolya Tak{\'a}cs and A. V{\'a}rkonyi-K{\'o}czy",
year = "2003",
doi = "10.1109/ISP.2003.1275809",
language = "English",
isbn = "0780378644",
pages = "31--36",
booktitle = "2003 IEEE International Symposium on Intelligent Signal Processing: From Classical Measurement to Computing with Perceptions, WISP 2003 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - SVD-based complexity reduction of "near PSGS" fuzzy systems

AU - Takács, Orsolya

AU - Várkonyi-Kóczy, A.

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

KW - Anytime systems

KW - Complexity reduction

KW - Fuzzy systems

UR - http://www.scopus.com/inward/record.url?scp=72449161478&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=72449161478&partnerID=8YFLogxK

U2 - 10.1109/ISP.2003.1275809

DO - 10.1109/ISP.2003.1275809

M3 - Conference contribution

AN - SCOPUS:72449161478

SN - 0780378644

SN - 9780780378643

SP - 31

EP - 36

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

PB - Institute of Electrical and Electronics Engineers Inc.

ER -