TY - JOUR AU - Baranyi, Péter Zoltán AU - Y, Yam AU - Várkonyiné Kóczy, Annamária AU - R J, Patton TI - SVD-based reduction to MISO TS models JF - IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS J2 - IEEE T IND ELECTRON VL - 50 PY - 2003 IS - 1 SP - 232 EP - 242 PG - 11 SN - 0278-0046 DO - 10.1109/TIE.2002.807673 UR - https://m2.mtmt.hu/api/publication/2235769 ID - 2235769 N1 - Cited By :39 Export Date: 11 April 2023 CODEN: ITIED Correspondence Address: Baranyi, P.; Dept. of Telecommun. and Telematics, , H-1111 Budapest, Hungary; email: baranyi@ttt-202.ttt.bme.hu LA - English DB - MTMT ER - TY - JOUR AU - Baranyi, Péter Zoltán AU - Várkonyiné Kóczy, Annamária TI - Adaptation of SVD Based Fuzzy Reduction via Minimal Expansion JF - IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT J2 - IEEE T INSTRUM MEAS VL - 51 PY - 2002 IS - 2 SP - 222 EP - 226 PG - 5 SN - 0018-9456 DO - 10.1109/19.997816 UR - https://m2.mtmt.hu/api/publication/2235770 ID - 2235770 N1 - Cited By :8 Export Date: 11 April 2023 CODEN: IEIMA Correspondence Address: Baranyi, P.; Integrated Intelligent Systems, , Budapest, Hungary; email: Baranyi@ttt-202.ttt.bme.hu AB - Most adopted fuzzy inference techniques do not hold the universal approximation property if the numbers of antecedent sets are limited. This fact and the exponential complexity problem of widely adopted fuzzy logic techniques show the contradictory features of fuzzy rule bases in pursuit of good approximation. As a result, complexity reduction emerged in fuzzy theory. The natural disadvantage of using complexity reduction is that the adaptivity property of the reduced approximation becomes highly restricted. This paper proposes a technique for singular value decomposition (SVD) based reduction developed in [1], which may alleviate the adaptivity restriction. LA - English DB - MTMT ER - TY - JOUR AU - Baranyi, Péter Zoltán AU - Yam, Y AU - Várkonyiné Kóczy, Annamária AU - Patton, RJ AU - Michelberger, Pál AU - Sugiyama, M TI - SVD-based Complexity Reduction to TS Fuzzy Models JF - IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS J2 - IEEE T IND ELECTRON VL - 49 PY - 2002 IS - 2 SP - 433 EP - 443 PG - 11 SN - 0278-0046 DO - 10.1109/41.993277 UR - https://m2.mtmt.hu/api/publication/2235743 ID - 2235743 AB - One of the typical important criteria to be considered in real-time control applications Is the computational complexity of the controllers, observers, and models applied. In this paper, a singular value decomposition (SVD)-based complexity reduction technique Is proposed for Takagi Sugeno (TS) fuzzy models. The main motivation is that the TS fuzzy model has exponentially growing computational complexity with the improvement of its approximation property through, as usually practiced, increasing the density of antecedent terms. The reduction technique proposed here Is capable of defining the contribution of each local linear model included in the TS fuzzy model, which serves to remove the weakly contributing ones as according to a given threshold. Reducing the number of models leads directly to the computational complexity reduction. This work also includes a number of numerical and application examples. LA - English DB - MTMT ER - TY - JOUR AU - Y, Yam AU - Baranyi, Péter Zoltán AU - C T, Yang TI - Reduction of Fuzzy Rule Base Via Singular Value Decomposition JF - IEEE TRANSACTIONS ON FUZZY SYSTEMS J2 - IEEE T FUZZY SYST VL - 7 PY - 1999 IS - 2 SP - 120 EP - 132 PG - 13 SN - 1063-6706 DO - 10.1109/91.755394 UR - https://m2.mtmt.hu/api/publication/2625220 ID - 2625220 N1 - Cited By :196 Export Date: 4 April 2023 CODEN: IEFSE Correspondence Address: Yam, Yeung; Chinese Univ of Hong Kong, Shatin, Hong Kong LA - English DB - MTMT ER - TY - CHAP AU - Kovács, Szilveszter AU - Kóczy, T. László ED - Reusch, Bernd TI - Application of the approximate fuzzy reasoning based on interpolation in the vague environment of the fuzzy rulebase in the fuzzy logic controlled path tracking strategy of differential steered AGVS T2 - Computational Intelligence Theory and Applications PB - Springer Netherlands CY - Berlin CY - Heidelberg SN - 9783540690313 T3 - Lecture Notes in Computer Science, ISSN 0302-9743 ; 1226. PY - 1997 SP - 456 EP - 467 PG - 12 DO - 10.1007/3-540-62868-1_138 UR - https://m2.mtmt.hu/api/publication/1053045 ID - 1053045 N1 - WoS:hiba:000073946500047 2020-01-08 10:30 befoglaló cím nem egyezik LA - English DB - MTMT ER - TY - JOUR AU - Kóczy, T. László AU - K, Hirota TI - Size Reduction by Interpolation in Fuzzy Rule Bases JF - IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS J2 - IEEE T SYST MAN CY B VL - 27 PY - 1997 SP - 14 EP - 25 PG - 12 SN - 1083-4419 DO - 10.1109/3477.552182 UR - https://m2.mtmt.hu/api/publication/1046191 ID - 1046191 N1 - IEEE, Hungary Department of Telecommunication and Telematics, Technical University of Budapest, Budapest, Hungary Department of Systems Science, Tokyo Institute of Technology, Yokohama 227, Japan Cited By :185 Export Date: 12 April 2023 CODEN: ITSCF Correspondence Address: Kóczy, L.T.; Department of Telecommunication and Telematics, , Budapest, Hungary AB - Fuzzy control is at present still the most important area of real applications for fuzzy theory. It is a generalized form of expert control using fuzzy sets in the definition of vague/linguistic predicates, modelling a system by If... then rules. In the classical approaches it is necessary that observations on the actual state of the system partly match (fire) one or several rules in the model (fired rules), and the conclusion is calculated by the evaluation of the degrees of matching and the fired rules. Interpolation helps reducing the complexity as it allows rule bases with gaps, Various interpolation approaches are shown. It is proposed that dense rule bases should be reduced so that only the minimal necessary number of rules remain still containing the essential information in the original base, and all other rules are replaced by the interpolation algorithm that however can recover them with a certain accuracy prescribed before reduction. The interpolation method used for demonstration is the Lagrange-method supplying the best fitting minimal degree polynomial, The paper concentrates on the reduction technique that is rather independent from the style of the interpolation model, but cannot be given in the form of a tractable algorithm. An example is shown to illustrate possible results and difficulties with the method. LA - English DB - MTMT ER -