HYPERBOLIC PARTICLE SWARM OPTIMIZATION WITH APPLICATION IN RATIONAL IDENTIFICATION

被引:0
|
作者
Kovacs, Peter [1 ]
Kiranyaz, Serkan [2 ]
Gabbouj, Moncef [2 ]
机构
[1] Eotvos Lorand Univ, H-1117 Budapest, Hungary
[2] Tampere Univ Technol, FIN-33101 Tampere, Finland
关键词
Rational functions; Malmquist-Takenaka system; Hyperbolic geometry; Particle swarm optimization;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The rational function systems proved to be useful in several areas including system and control theories and signal processing. In this paper, we present an extension of the well-known particle swarm optimization (PSO) method based on the hyperbolic geometry. We applied this method on digital signals to determine the optimal parameters of the rational function systems. Our goal is to minimize the error between the approximation and the original signal while the poles of the system remain stable. Namely, we show that the presented algorithm is suitable to localize the same poles by using different initial conditions.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Application of a particle swarm optimization for shape optimization in hydraulic machinery
    Moravcc, Prokop
    Rudolf, Pavel
    [J]. EXPERIMENTAL FLUID MECHANICS 2016 (EFM16 ), 2017, 143
  • [32] Application of particle swarm optimization in synthetic optimization of project schedule
    Huang, Yuansheng
    Zhang, Weina
    Qi, Jianxun
    [J]. DYNAMICS OF CONTINUOUS DISCRETE AND IMPULSIVE SYSTEMS-SERIES B-APPLICATIONS & ALGORITHMS, 2006, 13E : 3475 - 3479
  • [33] Particle swarm optimization and identification of inelastic material parameters
    Vaz, M., Jr.
    Cardoso, E. L.
    Stahlschmidt, J.
    [J]. ENGINEERING COMPUTATIONS, 2013, 30 (07) : 936 - 960
  • [34] Particle Swarm Optimization for Identification of a Flexible Manipulator System
    Yatim, Hanim
    Darus, Intan Z. Mat
    Hadi, Muhammad Sukri
    [J]. 2013 IEEE SYMPOSIUM ON COMPUTERS AND INFORMATICS (ISCI 2013), 2013,
  • [35] Moving Force Identification based on Particle Swarm Optimization
    Liu, Huanlin
    Yu, Ling
    [J]. 2016 12TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY (ICNC-FSKD), 2016, : 825 - 829
  • [36] Rational approximation for fractional-order system by particle swarm optimization
    Zhe Gao
    Xiaozhong Liao
    [J]. Nonlinear Dynamics, 2012, 67 : 1387 - 1395
  • [37] Spindle dynamics identification using particle swarm optimization
    Ganguly, Vasishta
    Schmitz, Tony L.
    [J]. JOURNAL OF MANUFACTURING PROCESSES, 2013, 15 (04) : 444 - 451
  • [38] Particle swarm optimization for identification of GMS friction model
    Nilkhamhang, Itthisek
    Sano, Akira
    [J]. 2006 SICE-ICASE INTERNATIONAL JOINT CONFERENCE, VOLS 1-13, 2006, : 2689 - +
  • [39] Identification of Structural Systems Using Particle Swarm Optimization
    Xue, Songtao
    Tang, Hesheng
    Zhou, Jin
    [J]. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING, 2009, 8 (02) : 517 - 524
  • [40] Particle swarm optimization with quantum infusion for system identification
    Luitel, Bipul
    Venayagamoorthy, Ganesh K.
    [J]. ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2010, 23 (05) : 635 - 649