@inproceedings{7a520a28bc5f47a18625e1ee950fd79d,
title = "Using RBF neural network for fault diagnosis in satellite ADS",
abstract = "In this paper, a new hybrid learning strategy composed of K-means clustering algorithm and Kalman filtering Is employed to train radial based function (RBF) neural network for fault diagnosis In satellite attitude determination system. Because Kalman filtering and K-means clustering algorithm both adopt linear update rule, their combination produces a new hybrid training algorithm that can converges quickly, Simulation results demonstrate that the proposed approach is effective for fault diagnosis In satellite attitude determination system.",
author = "Lin Cai and Yuancan Huang and Shaolin Lu and Jiabin Chen",
year = "2007",
doi = "10.1109/ICCA.2007.4376518",
language = "English",
isbn = "1424408180",
series = "2007 IEEE International Conference on Control and Automation, ICCA",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1052--1055",
booktitle = "2007 IEEE International Conference on Control and Automation, ICCA",
address = "United States",
note = "2007 IEEE International Conference on Control and Automation, ICCA ; Conference date: 30-05-2007 Through 01-06-2007",
}