Identification of linear models by fuzzy basis functions

被引：2
|
作者：
Demenkov, N. P. [1 ]
Mikrin, E. A. [1 ]
Mochalov, I. A. [1 ]
机构：
[1] Bauman Moscow State Tech Univ, Moscow, Russia
来源：
IFAC PAPERSONLINE | 2018年 / 51卷 / 32期
关键词：
hybrid data; fuzzy estimation; least squares method; fully fuzzy system of linear equations;
D O I：
10.1016/j.ifacol.2018.11.484
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This article reviews the application of the least squares method for the processing of hybrid data. We formulated and solved the problem of fuzzy estimation of the parameters of a model with fuzzy basis functions, during the solution of which fully fuzzy systems of linear equations appear. In order to illustrate the solution of the problem by the inverse matrix method, two fuzzy basis functions are reviewed: fuzzy unit and fuzzy linear dependence. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.
引用
收藏
页码：574 / 579
页数：6
相关论文
共 50 条
  • [31] Application of Triangular and Delta Basis Functions to Solve Linear Fredholm Fuzzy Integral Equation of the Second Kind
    Mirzaee, Farshid
    Paripour, Mahmoud
    Yari, Mohammad Komak
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2014, 39 (05) : 3969 - 3978
  • [32] Application of Triangular and Delta Basis Functions to Solve Linear Fredholm Fuzzy Integral Equation of the Second Kind
    Farshid Mirzaee
    Mahmoud Paripour
    Mohammad Komak Yari
    Arabian Journal for Science and Engineering, 2014, 39 : 3969 - 3978
  • [33] STATISTICAL FUZZY APPROXIMATION TO FUZZY DIFFERENTIABLE FUNCTIONS BY FUZZY LINEAR OPERATORS
    Duman, Oktay
    HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS, 2010, 39 (04): : 497 - 514
  • [34] AN IDENTIFICATION ALGORITHM OF FUZZY MODELS
    张化光
    陈来九
    徐治皋
    Journal of Southeast University(English Edition), 1992, (02) : 54 - 63
  • [35] Fuzzy models, identification and applications
    Kóczy, LT
    Botzheim, J
    ICCC 2005: IEEE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL CYBERNETICS, 2005, : 13 - 19
  • [36] Fuzzy models for system identification
    Sánchez-Yañez, RE
    Ayala-Ramírez, V
    Jaime-Rivas, R
    2003 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS, VOLS 1-5, CONFERENCE PROCEEDINGS, 2003, : 3330 - 3335
  • [37] IDENTIFICATION OF DYNAMIC FUZZY MODELS
    CAO, SG
    REES, NW
    FUZZY SETS AND SYSTEMS, 1995, 74 (03) : 307 - 320
  • [38] Review of fuzzy system models with an emphasis on fuzzy functions
    Tuerksen, I. Burhan
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2009, 31 (01) : 7 - 31
  • [39] An experimental nonlinear system identification based on local linear neuro-fuzzy models
    Nourzadeh, Hamidreza
    Fatehi, Alireza
    Labibi, Batool
    Araabi, Babak Nadjar
    2006 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL TECHNOLOGY, VOLS 1-6, 2006, : 2577 - +
  • [40] Identification of quadratic non linear systems using higher order statistics and fuzzy models
    Antari, Jilali
    Iqdour, Radouane
    Safi, Said
    Zeroual, Abdelouhab
    Lyhyaoui, Abdelouahid
    2006 IEEE International Conference on Acoustics, Speech and Signal Processing, Vols 1-13, 2006, : 3163 - 3166
12345