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
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