@inproceedings{bce37db427a24b68b6373ab1a82bf7df,
title = "The adaptive learning rates of extended Kalman filter based training algorithm for wavelet neural networks",
abstract = "Since the convergence of neural networks depends on learning rates, the learning rates of training algorithm for neural networks are very important factors. Therefore, we propose the Adaptive Learning Rates(ALRs) of Extended Kalman Filter(EKF) based training algorithm for wavelet neural networks(WNNs). The ALRs of the EFK based training algorithm produce the convergence of the WNN. Also we derive the convergence analysis of the learning process from the discrete Lyapunov stability theorem. Several simulation results show that the EKF based WNN with ALRs adapt to abrupt change and high nonlinearity with satisfactory performance.",
author = "Kyoung, {Joo Kim} and Jin, {Bae Park} and Yoon, {Ho Choi}",
year = "2006",
language = "English",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "327--337",
booktitle = "MICAI 2006",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}