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Volumn , Issue , 2008, Pages 434-439

Adaptive nonlinear system identification using comprehensive learning PSO

Author keywords

[No Author keywords available]

Indexed keywords

BOOLEAN FUNCTIONS; COMPUTATIONAL METHODS; COMPUTER NETWORKS; COMPUTER SIMULATION; CONTROL SYSTEM ANALYSIS; CONTROL THEORY; DIESEL ENGINES; EVOLUTIONARY ALGORITHMS; GENETIC ALGORITHMS; NEURAL NETWORKS; NONLINEAR ANALYSIS; NONLINEAR SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; SIGNAL PROCESSING; SPEED;

EID: 51049088828     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISCCSP.2008.4537265     Document Type: Conference Paper
Times cited : (13)

References (14)
  • 1
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    • Haykin, S.1
  • 2
    • 51049112548 scopus 로고    scopus 로고
    • B. Widrow and S. D. Sterns, Adaptive Signal Processing , Pearson Education, pp. 22, Inc. 1985.
    • B. Widrow and S. D. Sterns, "Adaptive Signal Processing" , Pearson Education, pp. 22, Inc. 1985.
  • 3
    • 0028053379 scopus 로고    scopus 로고
    • Brouwn , G.G ; Krijgsman , A.J, Hybrid Neural networks for nonlinear system identification, IEEE International conference On Control, 1, 21-24 March 94
    • Brouwn , G.G ; Krijgsman , A.J, "Hybrid Neural networks for nonlinear system identification, IEEE International conference On Control, volume 1, 21-24 March 94
  • 4
    • 51049100242 scopus 로고    scopus 로고
    • Chen , J.R ; Mars , P , 'The feasibility of using MLP networks for system identification' IEE colloquium on Neural Networks for systems: Principles and applications, Pages: 3/1-3/3 , 25 Jan 1991.
    • Chen , J.R ; Mars , P , 'The feasibility of using MLP networks for system identification' IEE colloquium on Neural Networks for systems: Principles and applications, Pages: 3/1-3/3 , 25 Jan 1991.
  • 6
    • 84968713158 scopus 로고    scopus 로고
    • Nonlinear system identification using Genetic algorithm Industrial Electronics Society, IECON 2000
    • 22-28 Oct, Pages, 4
    • Kumon, T. Iwasaki, M., Suzuki, T., Hashiyama, T.; Matsui, N., Okuma, S., "Nonlinear system identification using Genetic algorithm" Industrial Electronics Society, IECON 2000. 26th Annual Conference of the IEEE - Volume 4, 22-28 Oct. 2000 Page(s):2485-2491 vol.4, 2000.
    • (2000) 26th Annual Conference of the IEEE , vol.4 , pp. 2485-2491
    • Kumon, T.1    Iwasaki, M.2    Suzuki, T.3    Hashiyama, T.4    Matsui, N.5    Okuma, S.6
  • 8
    • 29844453780 scopus 로고    scopus 로고
    • Identification for non-linear systems based on particle swarm optimization and recurrent neural network [ultrasonic motor control applications]
    • _, 27-30 May 2005 Pages
    • Ge Hongwei, Liang Yanchun, _"Identification for non-linear systems based on particle swarm optimization and recurrent neural network [ultrasonic motor control applications] " , Proc. International conference on communications, circuits and systems, Vol. 2, 27-30 May 2005 Page(s).
    • Proc. International conference on communications, circuits and systems , vol.2
    • Ge, H.1    Liang, Y.2
  • 10
    • 51049119282 scopus 로고    scopus 로고
    • _J. J. Liang, A. K. Qin, Ponnuthurai Nagaratnam Suganthan,S. Baskar_, Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions, IEEE Transactions on evolutionary computation
    • _J. J. Liang, A. K. Qin, Ponnuthurai Nagaratnam Suganthan,S. Baskar_, "Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions", IEEE Transactions on evolutionary computation
  • 11
    • 0029483769 scopus 로고
    • Nonlinear black-box modeling in system identification : A unified overview
    • J. Sjoberg, Q. Zhang et.al. : Nonlinear black-box modeling in system identification : a unified overview, Automatica, Vol.31, No.12, pp.1691-1724, 1995.
    • (1995) Automatica , vol.31 , Issue.12 , pp. 1691-1724
    • Sjoberg, J.1    Zhang, Q.2
  • 14
    • 15344349596 scopus 로고    scopus 로고
    • Passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems
    • Hayakawa T, Haddad WM, Bailey JM, Hovakimyan N. Passivity-based neural network adaptive output feedback control for nonlinear nonnegative dynamical systems. IEEE Transactions on Neural Networks 2005; 16(2):387-398.
    • (2005) IEEE Transactions on Neural Networks , vol.16 , Issue.2 , pp. 387-398
    • Hayakawa, T.1    Haddad, W.M.2    Bailey, J.M.3    Hovakimyan, N.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.