Nonlinear Statistical Process Monitoring based on Competitive Principal Component Analysis
暂无分享,去创建一个
[1] John F. MacGregor. STATISTICAL PROCESS CONTROL OF MULTIVARIATE PROCESSES , 1994 .
[2] J. E. Jackson,et al. Control Procedures for Residuals Associated With Principal Component Analysis , 1979 .
[3] Sam T. Roweis,et al. EM Algorithms for PCA and SPCA , 1997, NIPS.
[4] T. Hastie,et al. Principal Curves , 2007 .
[5] Andrew R. Webb. An approach to non-linear principal components analysis using radially symmetric kernel functions , 1996, Stat. Comput..
[6] Silvio Simani,et al. Model-based fault diagnosis in dynamic systems using identification techniques , 2003 .
[7] Janos Gertler,et al. A new structural framework for parity equation-based failure detection and isolation , 1990, Autom..
[8] Thomas F. Edgar,et al. Use of principal component analysis for sensor fault identification , 1996 .
[9] Nanda Kambhatla,et al. Dimension Reduction by Local Principal Component Analysis , 1997, Neural Computation.
[10] James C. Bezdek,et al. Pattern Recognition with Fuzzy Objective Function Algorithms , 1981, Advanced Applications in Pattern Recognition.
[11] Thomas J. McAvoy,et al. Nonlinear PLS Modeling Using Neural Networks , 1992 .
[12] Rolf Isermann,et al. Supervision, fault-detection and fault-diagnosis methods — An introduction , 1997 .
[13] Paul M. Frank,et al. Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy: A survey and some new results , 1990, Autom..
[14] Jin Cao,et al. Partial PCA-based optimal structured residual design for fault isolation , 2004, Proceedings of the 2004 American Control Conference.
[15] Weihua Li,et al. Isolation enhanced principal component analysis , 1999 .
[16] Janos Gertler,et al. Fault detection and diagnosis in engineering systems , 1998 .
[17] Mark A. Kramer,et al. Autoassociative neural networks , 1992 .
[18] G. Box. Some Theorems on Quadratic Forms Applied in the Study of Analysis of Variance Problems, I. Effect of Inequality of Variance in the One-Way Classification , 1954 .
[19] George W. Irwin,et al. RBF principal manifolds for process monitoring , 1999, IEEE Trans. Neural Networks.
[20] Geoffrey E. Hinton,et al. Modeling the manifolds of images of handwritten digits , 1997, IEEE Trans. Neural Networks.
[21] Michael E. Tipping,et al. Probabilistic Principal Component Analysis , 1999 .
[22] Christopher M. Bishop,et al. Mixtures of Probabilistic Principal Component Analyzers , 1999, Neural Computation.
[23] T. J. McAvov,et al. BASE CONTROL FOR THE TENNESSEE EASTMAN PROBLEM , 2001 .
[24] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .