Kernel Fisher discriminant analysis using feature vector selection for fault diagnosis

Proceedings - 2008 2nd International Symposium on Intelligent Information Technology Application, IITA 2008

Volumn 3, Issue , 2008, Pages 109-113

  Wu, Hongyan ^a,b   Huang, Daoping ^a  

^a SOUTH CHINA UNIVERSITY OF TECHNOLOGY   (China)

^b LINGNAN NORMAL UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; COMPUTATIONAL GEOMETRY; DISCRIMINANT ANALYSIS; FISHER INFORMATION MATRIX; IMAGE RETRIEVAL; INFORMATION TECHNOLOGY; LEARNING ALGORITHMS; PROCESS MONITORING;

FAULT DIAGNOSIS; FEATURE VECTOR SELECTIONS; FISHER DISCRIMINANT ANALYSIS; GEOMETRICAL STRUCTURES; IN-PROCESS MONITORING; KERNEL FISHER DISCRIMINANT ANALYSIS; PATTERN RECOGNITION AND CLASSIFICATIONS; TENNESSEE EASTMAN PROCESS; WAVELET DE-NOISING;

FACE RECOGNITION;

EID: 62949162722     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IITA.2008.172     Document Type: Conference Paper

References (13)

1. F. Akbaryan, P.R. Bishnoi, "Fault diagnosis of multivariate systems using pattern recognition and multisensor data analysis technique", Computers and Chemical Engineering, 25, 2001, pp. 1313-1339.
2. L.H. Chiang, E.L. Russell, R.D. Braatz, "Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis", Chemometrics and intelligent laboratory systems, (50) 2000, pp. 243-252.
3. G. Lee, C. H. Han, E. S. Yoon, "Multiple-fault diagnosis of the Tennessee Eastman process based on system decomposition and dynamic PLS", Industrial & Engineering Chemistry Research, (43)2004, pp. 8037-8048.
4. W. S. Chen, P. C. Yuen, J. Huang, et al. "Kernel machine-based one-parameter regularized Fisher discriminant method for face recognition", IEEE Transactions on Systems, Man, and Cybernetics-PartB: Cybernetics, 35(4), 2005, pp. 659-669.
5. G. Baudat, F. Anouar, "Generalized discriminant analysis using a kernel approach", Neural Computation, 12(10), 2000, pp. 2385-2404.
6. G.C. Cawley, N.L.C. Talbot, "Efficient leave-one-out cross-validation of kernel Fisher discriminant classifiers", Pattern Recognition, 36(11), 2003, pp. 2585-2592.
7. S.A. Billings, K.L. Lee, "Nonlinear Fisher discriminant analysis using a minimum squared error cost function and the orthogonal least squares algorithm", Neural network, 15(2), 2002, pp. 263-270.
8. K.A. Kosanovich, M.J. Piovoso, "PCA of wavelet transformed process data for monitoring", intelligent data analysis, (1) 1997, p. 85-99.
9. P. Teppola, P. Minkkinen, "Wavelet-PLS regression models for both exploratory data analysis and process monitoring", Journal of Chemometrics, (14) 2000, pp. 383-399.
10. G. Baudat, F. Anouar, "Kernel-based methods and function approximation", Neural Computation, 12(10), 2000, pp. 2385-2404
11. DL Donoho, "De-nosing by soft-thresholding", [J]. IEEE Transactions on Information Theory, 41 (3), 1995, pp. 613-627.
12. D. Gnanadurai, V. Sadasivam, "An efficient adaptive thresholding technique for wavelet based image de-noising", Int. J. Sig. Proc, 2(2), 2005, pp. 114-119.
13. J.H. Downs, E.F. Vogel, "plant-wide industrial process control problem", Computers Chemical Engineering, 17(3), 1993, pp. 245-255.