@inproceedings{5b0596e8092a40b5a49dbc52481161b2,
title = "A kernel-based bayesian classifier for fault detection and classification",
abstract = "A kernel constructed by Shannon sampling function was utilized for kernel Fisher discriminant analysis (KFDA). And kernel-based Bayesian decision function was implemented for fault detection. Simultaneously, Bhattacharyya distance was introduced as a criterion function for separability comparison. The proposed Shannon KFDA was compared with Gaussian KFDA on Tennessee Eastman Process (TEP) data. The results show that Shannon KFDA has lager Bhattacharyya distance and detects more faults more quickly than Gaussian KFDA.",
keywords = "Fault detection, Kernel fisher discriminant analysis, Kernel function construction, Kernel-based bayesian decision function",
author = "Chunmei Yu and Quan Pan and Yongmei Cheng and Hongcai Zhang",
year = "2008",
doi = "10.1109/WCICA.2008.4592910",
language = "英语",
isbn = "9781424421145",
series = "Proceedings of the World Congress on Intelligent Control and Automation (WCICA)",
pages = "124--128",
booktitle = "Proceedings of the 7th World Congress on Intelligent Control and Automation, WCICA'08",
note = "7th World Congress on Intelligent Control and Automation, WCICA'08 ; Conference date: 25-06-2008 Through 27-06-2008",
}