Designing Interval Type-2 Fuzzy Logic Systems Using an SVD-QR Method: Rule Reduction

International Journal of Intelligent Systems

Volumn 15, Issue 10, 2000, Pages 939-957

  Liang, Qilian ^a   Mendel, Jerry M ^a  

^a University of Southern California   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0345808516     PISSN: 08848173     EISSN: None     Source Type: Journal    
DOI: 10.1002/1098-111X(200010)15:10<939::AID-INT3>3.0.CO;2-G     Document Type: Article

References (19)

1. Karnik NN, Mendel JM, Liang Q. Type-2 fuzzy logic systems. IEEE Trans Fuzzy Systems 1999;7:643-658.
2. Wang L-X, Mendel JM. Fuzzy basis functions, universal approximation, and orthogonal least squares learning. IEEE Trans Neural Networks 1992;3:807-814.
3. Yen J, Wang L. Simplification of fuzzy rule based systems using orthogonal transformation. In: Proc. of IEEE 6th Int'l Conf. on Fuzzy Systems. Barcelona, Spain; July 1997. p 253-258.
4. Comon P, Golub GH. Tracking a few extreme singular values and vectors in signal processing. Proc IEEE 1990;78:1327-1343.
5. van der Veen A-J, Deprettere EF, Swindlehurst AL. Subspace-based signal analysis using singular value decomposition. Proc IEEE 1993;81:1277-1308.
6. Mouzouris GC, Mendel JM. Designing fuzzy logic systems for uncertain environments using a singular-value-QR decomposition method. In: Proc of IEEE 5th Int'l. Conf. on Fuzzy Systems. New Orleans, LA; 1996. p 295-301.
7. Mouzouris GC, Mendel JM. A singular-value-QR decomposition based method for training fuzzy logic systems in uncertain environments. J Intell Fuzzy Systems 1997;5:367-374.
8. Yen J, Wang L. An SVD-based fuzzy model reduction strategy. In: Proc. of IEEE 5th Int'l. Conf. on Fuzzy Systems. New Orleans, LA; 1996. p 835-841.
9. Yam Y, Baranyi P, Yang C-T. Reduction of fuzzy rule base via singular value decomposition. IEEE Trans Fuzzy Systems 1999;7:120-132.
10. Liang Q, Mendel JM. Interval type-2 fuzzy logic systems: theory and design. IEEE Trans Fuzzy Systems, accepted.
11. Karnik NN, Mendel JM. An Introduction to Type-2 Fuzzy Logic Systems; USC Report; 1998. http://sipi.usc.edu/~mendel/report.
12. Karnik NN, Mendel JM. Type-2 fuzzy logic systems: type-reduction. In: Proc. of 1998 IEEE SMC Conference. San Diego, CA; 1998. p 2046-2051.
13. Karnik NN, Mendel JM. Centroid of a type-2 fuzzy set. Information Sci, submitted.
14. Mendel JM. Fuzzy logic systems for engineering: a tutorial. Proc IEEE 1995;83: 345-377.
15. Mackey MC, Glass L. Oscillation and chaos in physiological control systems. Science 1987;197:287-289.
16. Golub GH, Van Loan CF. Matrix computations. Baltimore, MD: Johns Hopkins University Press; 1983.
17. Yen J, Langari R, Wang L. Principal components, B-splines, and fuzzy system reduction. Int J Uncertainty Fuzziness Knowledge-Based Systems 1996;4:561-572.
18. Zadeh LA. The concept of a linguistic variable and its application to approximate reasoning - I. Information Sci 1975;8:199-249.
19. Wang L-X, Mendel JM. Back-propagation of fuzzy systems as non-linear dynamic system identifiers. In: Proc. IEEE Int'l. Conf. on Fuzzy Systems. San Diego, CA; 1992. p 1409-1418.