1 K. Wang, "The combined use of order tracking techniques for enhanced Fourier analysis of order components" 25 (25): 803-811, 2011
2 M. Döhlera, "Subspace-based fault detection robust to changes in the noise covariances" 49 (49): 2734-2743, 2013
3 M. Döhlera, "Subspace-based damage detection under changes in the ambient excitation statistics" 45 (45): 207-224, 2014
4 Zeng Liao, "Subspace Identification for Fractional Order Hammerstein Systems Based on Instrumental Variables" 제어·로봇·시스템학회 10 (10): 947-953, 2012
5 Alejandro J. Rojas, "Step Reference Tracking in Signal-to-noise Ratio Constrained Feedback Control" 제어·로봇·시스템학회 13 (13): 1131-1139, 2015
6 D. Balvay, "Signal-to-noise ratio improvement in dynamic contrastenhanced CT and MR imaging with automated principal component analysis filtering" 258 (258): 435-445, 2011
7 M. F. Yaqub, "Severity invariant feature selection for machine health monitoring" 6 (6): 238-248, 2011
8 X. Wei1, "Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques" 24 (24): 687-707, 2010
9 T. He, "Process fault detection and diagnosis based on principal component analysis" 3551-3556, 2006
10 F. Pedersen, "Principal component analysis of dynamic positron emission tomography images" 21 (21): 1285-1292, 1994
1 K. Wang, "The combined use of order tracking techniques for enhanced Fourier analysis of order components" 25 (25): 803-811, 2011
2 M. Döhlera, "Subspace-based fault detection robust to changes in the noise covariances" 49 (49): 2734-2743, 2013
3 M. Döhlera, "Subspace-based damage detection under changes in the ambient excitation statistics" 45 (45): 207-224, 2014
4 Zeng Liao, "Subspace Identification for Fractional Order Hammerstein Systems Based on Instrumental Variables" 제어·로봇·시스템학회 10 (10): 947-953, 2012
5 Alejandro J. Rojas, "Step Reference Tracking in Signal-to-noise Ratio Constrained Feedback Control" 제어·로봇·시스템학회 13 (13): 1131-1139, 2015
6 D. Balvay, "Signal-to-noise ratio improvement in dynamic contrastenhanced CT and MR imaging with automated principal component analysis filtering" 258 (258): 435-445, 2011
7 M. F. Yaqub, "Severity invariant feature selection for machine health monitoring" 6 (6): 238-248, 2011
8 X. Wei1, "Sensor fault detection and isolation for wind turbines based on subspace identification and Kalman filter techniques" 24 (24): 687-707, 2010
9 T. He, "Process fault detection and diagnosis based on principal component analysis" 3551-3556, 2006
10 F. Pedersen, "Principal component analysis of dynamic positron emission tomography images" 21 (21): 1285-1292, 1994
11 I. T. Joliffe, "Principal component analysis and exploratory factor analysis" 1 (1): 69-95, 1992
12 S. J. Zhao, "Performance monitoring of processes with multiple operating modes through multiple PLS models" 16 (16): 763-772, 2006
13 T. Thireou, "Performance evaluation of principal component analysis in dynamic FDG-PET studies of recurrent colorectal cancer" 27 (27): 43-51, 2003
14 B. Diebold, "Optimization of factor analysis of the left ventricle in echocardiography for detecting wall motion abnormalities" 31 (31): 1597-1606, 2005
15 W. Xun, "Nonlinear PCA with the local approach for diesel engine fault detection and diagnosis" 16 (16): 122-129, 2008
16 W. L. Qun, "Noise removal based on filtered principal component reconstruction" 58 (58): 589-598, 2015
17 S. V. Nuffel, "Multivariate analysis of 3D ToF-SIMS images : method validation and application to cultured neuronal networks" 141 (141): 90-95, 2016
18 M. F. Yaqub, "Machine health monitoring based on stationary wavelet transform and 4th order cumulants" 9 (9): 55-64, 2012
19 C. Dougherty, "Introduction to Econometrics" Oxford University Press 2002
20 M. F. Yaqub, "Inchoate fault detection framework : adaptive selection of wavelet nodes and cumulant orders" 61 (61): 685-695, 2012
21 M. Hamadache, "Improving signal-to-noise ratio(SNR)for inchoate fault detection based on principal component analysis(PCA)" 561-566, 2014
22 S. Pyatykh, "Image noise level estimation by principal component analysis" 22 (22): 687-699, 2013
23 Y. Anzai, "Head and neck cancer : detection of recurrence with threedimensional principal components analysis at dynamic FDG PET" 212 (212): 285-290, 1999
24 G. Noyel, "Filtering, segmentation and region classification by hyperspectral mathematical morphology of DCE-MRI series for angiogenesis imaging" 1517-1520, 2008
25 D. Garcia-Alvarez, "Fault detection and isolation in transient states using principal component analysis" 22 (22): 551-563, 2012
26 B. Williams, "Exploratory factor analysis-A five-step guide for novices" 8 (8): 1-14, 2012
27 김규진, "Directional Pedestrian Counting with a Hybrid Map-based Model" 제어·로봇·시스템학회 13 (13): 201-211, 2015
28 J. V. Manjon, "Diffusion weighted image denoising using overcomplete local PCA" 8 (8): e73021-, 2013
29 Anissa Benaicha, "Determination of Principal Component Analysis Models for Sensor Fault Detection and Isolation" 제어·로봇·시스템학회 11 (11): 296-305, 2013
30 A. de Cheveigné, "Denoising based on time-shift PCA" 165 (165): 297-305, 2007
31 J. Chen, "Data-driven subspace-based adaptive fault detection for solar power generation systems" 7 (7): 1498-1508, 2013
32 Y. Ding, "Application of the Karhunen-Loeve transform temporal image ?lter to reduce noise in real-time cardiac cine MRI" 54 (54): 3909-3922, 2009
33 R. Z. Morawski, "Application of principal components analysis and signal-to-noise ratio for calibration of spectrophotometric analysers of food" 79 : 302-310, 2016
34 P. Dubey, "A survey paper on noise estimation and removal through principal component analysis" 3 (3): 364-366, 2013
35 K. Hermus, "A review of signal subspace speech enhancement and its application to noise robust speech recognition" 2007 (2007): 195-195, 2007
36 Mahendra Kumar Samal, "A Computationally Efficient Approach for NN Based System Identification of a Rotary Wing UAV" 제어·로봇·시스템학회 8 (8): 727-734, 2010