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
Link To Document :
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