DocumentCode :
423648
Title :
The application of OBE to neural networks
Author :
Jiang, Yan ; He, Qing ; Tong, Tiaosheng ; Dilger, Werner
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
Volume :
2
fYear :
2004
fDate :
25-29 July 2004
Firstpage :
961
Abstract :
In 1989, Singhal and Wu showed that training a feed forward neural network can be viewed as an identification problem for a nonlinear dynamic system using an extended Kalman filter algorithm, which can converge in few iterations. In this paper, a new type of optimal bounding ellipsoid (OBE) algorithm is presented, which is a set-membership identification algorithm based on set theory, and it is shown how it can be used for training feedforward neural networks. The algorithm is compared with backpropagation (BP) and extended Kalman filter (EKF) algorithms and simulation results are presented.
Keywords :
Kalman filters; backpropagation; convergence of numerical methods; feedforward neural nets; identification; iterative methods; nonlinear dynamical systems; set theory; BP algorithm; EKF algorithm; backpropagation algorithm; convergence; extended Kalman filter algorithm; feedforward neural networks; iterative methods; neural network training; nonlinear dynamical system; optimal bounding ellipsoid algorithm; set theory; set-membership identification algorithm; Artificial neural networks; Convergence; Educational institutions; Ellipsoids; Feedforward neural networks; Feedforward systems; Neural networks; Noise measurement; Nonlinear equations; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on
ISSN :
1098-7576
Print_ISBN :
0-7803-8359-1
Type :
conf
DOI :
10.1109/IJCNN.2004.1380063
Filename :
1380063
Link To Document :
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