@inproceedings{3e4fb0b385864528b00859b1ab716f37,
title = "KPCA plus FDA for fault detection",
abstract = "Kernel principal component analysis (KPCA) is widely used for fault detection. In this paper, a KPCA plus Fisher discriminant analysis (FDA) scheme is adopted to improve the fault detection performance of KPCA. Simulation results are given to show the effectiveness of the improvements for fault detection performance in terms of high fault detection rate.",
author = "Cui Peiling and Fang Jiancheng",
year = "2007",
language = "英语",
isbn = "9783540723943",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 3",
pages = "597--606",
booktitle = "Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings",
edition = "PART 3",
note = "4th International Symposium on Neural Networks, ISNN 2007 ; Conference date: 03-06-2007 Through 07-06-2007",
}