A fast U-D factorization-based learning algorithm with applications to nonlinear system modeling and identification

@article{Zhang1999AFU,
  title={A fast U-D factorization-based learning algorithm with applications to nonlinear system modeling and identification},
  author={Youmin Zhang and X. Rong Li},
  journal={IEEE transactions on neural networks},
  year={1999},
  volume={10 4},
  pages={
          930-8
        }
}
A fast learning algorithm for training multilayer feedforward neural networks (FNN's) by using a fading memory extended Kalman filter (FMEKF) is presented first, along with a technique using a self-adjusting time-varying forgetting factor. Then a U-D factorization-based FMEKF is proposed to further improve the learning rate and accuracy of the FNN. In comparison with the backpropagation (BP) and existing EKF-based learning algorithms, the proposed U-D factorization-based FMEKF algorithm… CONTINUE READING
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