The application of OBE to neural networks

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.