• DocumentCode
    3221689
  • Title

    Design for Self-Organizing Fuzzy Neural Network with Extended Kalman Filter

  • Author

    Liu, Fan ; Er, Meng Joo

  • Author_Institution
    Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore
  • fYear
    2010
  • fDate
    9-11 June 2010
  • Firstpage
    423
  • Lastpage
    427
  • Abstract
    In this paper, a Self-organizing Fuzzy Neural Network employing an Extended Kalman Filter (EKF), termed Self-organizing Fuzzy Neural Networks with Extended Kalman Filter (SOFNNEKF) is designed and developed. The learning algorithm based on an EKF is simple and effective and is able to generate a fuzzy neural network with a high accuracy and compact structure. The structure learning of the SOFNNEKF, based on adding and pruning techniques is proposed. The EKF algorithm is used to adjust free parameters of the SOFNNEKF. Simulation and comparative studies with other methods demonstrate that a more compact structure with high performance can be achieved by the proposed algorithm.
  • Keywords
    Kalman filters; control system synthesis; fuzzy neural nets; learning (artificial intelligence); nonlinear filters; self-organising feature maps; EKF; FNN; extended Kalman filter; learning algorithm; self-organizing fuzzy neural network design; Automatic control; Design automation; Fuzzy control; Fuzzy logic; Fuzzy neural networks; Fuzzy systems; Neural networks; Neurons; Radio access networks; Resource management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Automation (ICCA), 2010 8th IEEE International Conference on
  • Conference_Location
    Xiamen
  • ISSN
    1948-3449
  • Print_ISBN
    978-1-4244-5195-1
  • Electronic_ISBN
    1948-3449
  • Type

    conf

  • DOI
    10.1109/ICCA.2010.5524416
  • Filename
    5524416