Improved kernel fisher discriminant analysis for fault diagnosis
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[1] George W. Irwin,et al. Improved reliability in diagnosing faults using multivariate statistics , 2006, Comput. Chem. Eng..
[2] M. Zuo,et al. Feature separation using ICA for a one-dimensional time series and its application in fault detection , 2005 .
[3] Sachin C. Patwardhan,et al. FAULT DETECTION AND ISOLATION USING CORRESPONDENCE ANALYSIS , 2005 .
[4] Kwang-Jae Kim,et al. Fault diagnosis of batch processes using discriminant model , 2004 .
[5] Nello Cristianini,et al. Spectral Kernel Methods for Clustering , 2001, NIPS.
[6] Gülnur Birol,et al. A modular simulation package for fed-batch fermentation: penicillin production , 2002 .
[7] In-Beum Lee,et al. Nonlinear dynamic process monitoring based on dynamic kernel PCA , 2004 .
[8] Hanqing Lu,et al. Improving kernel Fisher discriminant analysis for face recognition , 2004, IEEE Transactions on Circuits and Systems for Video Technology.
[9] Nola D. Tracy,et al. Multivariate Control Charts for Individual Observations , 1992 .
[10] G. Baudat,et al. Kernel-based methods and function approximation , 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).
[11] C. Yoo,et al. Nonlinear process monitoring using kernel principal component analysis , 2004 .
[12] Junhong Li,et al. Improved kernel principal component analysis for fault detection , 2008, Expert Syst. Appl..
[13] B. Scholkopf,et al. Fisher discriminant analysis with kernels , 1999, Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (Cat. No.98TH8468).
[14] Leo H. Chiang,et al. Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis , 2000 .
[15] Furong Gao,et al. Combination method of principal component and wavelet analysis for multivariate process monitoring and fault diagnosis , 2003 .
[16] Jian Huang,et al. Kernel machine-based one-parameter regularized Fisher discriminant method for face recognition , 2005, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).
[17] G. Baudat,et al. Generalized Discriminant Analysis Using a Kernel Approach , 2000, Neural Computation.
[18] D. Thukaram,et al. Artificial neural network and support vector Machine approach for locating faults in radial distribution systems , 2005, IEEE Transactions on Power Delivery.
[19] Cheng Haozhong,et al. Fault diagnosis of power transformer based on multi-layer SVM classifier , 2005 .
[20] Hyun-Woo Cho,et al. Identification of contributing variables using kernel-based discriminant modeling and reconstruction , 2007, Expert Syst. Appl..
[21] Junghui Chen,et al. On-line batch process monitoring using MHMT-based MPCA , 2006 .
[22] Stan Z. Li,et al. Face recognition using the nearest feature line method , 1999, IEEE Trans. Neural Networks.
[23] Xiaoou Tang,et al. Kernel scatter-difference based discriminant analysis for face recognition , 2004, Proceedings of the 17th International Conference on Pattern Recognition, 2004. ICPR 2004..
[24] Hyun-Woo Cho. An orthogonally filtered tree classifier based on nonlinear kernel-based optimal representation of data , 2008, Expert Syst. Appl..
[25] Bernhard Schölkopf,et al. Nonlinear Component Analysis as a Kernel Eigenvalue Problem , 1998, Neural Computation.
[26] Gibaek Lee,et al. Multiple-Fault Diagnosis of the Tennessee Eastman Process Based on System Decomposition and Dynamic PLS , 2004 .
[27] Hyun-Woo Cho. Nonlinear feature extraction and classification of multivariate data in kernel feature space , 2007, Expert Syst. Appl..
[28] Jin Hyun Park,et al. Fault detection and identification of nonlinear processes based on kernel PCA , 2005 .
[29] ChangKyoo Yoo,et al. Statistical monitoring of dynamic processes based on dynamic independent component analysis , 2004 .
[30] In-Beum Lee,et al. Fault identification for process monitoring using kernel principal component analysis , 2005 .