1 |
Bayissa, W. L., Haritos, N., and Thelandersson, S. (2008), Vibration-based structural damage identification using wavelet transformation, Mechanical Systems and Signal Processing, 22, 1194-1215.
DOI
|
2 |
Bishop, C. M. (2006), Pattern recognition and machine learning, Springer.
|
3 |
Guo, H., Jack, L. B.m and Nandi, A. K. (2005), Feature generation using genetic programming with application to fault classification, IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 35(1), 89-99.
DOI
|
4 |
Hastie, T., Tibshirani, R., and Friedman, J. (2001), The elements of statistical learning, New York: Springer.
|
5 |
Hitchon, W. N. G. (1999), Plasma processing for semiconductor fabrication, Cambridge University Press.
|
6 |
Hong, S. J. and May, G. S. (2005), Neural-network-based sensor fusion of optical emission and mass spectroscopy data for real-time fault detection in reactive ion etching, IEEE Transactions on Industrial Electronics, 52(4), 1063-1072.
DOI
|
7 |
Hong, S. J., May, G. S., Park, D.-C. (2003), Neural network modeling of reactive ion etching using optical emission spectroscopy data, IEEE Transactions on Semiconductor Manufacturing, 16(4), 598-608.
DOI
|
8 |
Hwang, S., Jeong, M. K., and Yum, B. J. (2014), Robust relevance vector machine with variational inference for improving virtual metrology accuracy, IEEE Transactions on Semiconductor Manufacturing, 27 (1), 83-94.
DOI
|
9 |
Kim, B., Bae, J. K., and Hong, W.-S. (2005), Plasma control using neural network and optical emission spectroscopy, Journal of Vacuum Science and Technology A, 23(2), 355-358.
DOI
|
10 |
Kim, B. and Kim, S. (2005), Diagnosis of plasma proces- sing equipment using neural network recognition of wavelet-filtered impedance matching, Microelectronic Engineering, 82, 44-52.
DOI
|
11 |
Kim, B. and Kim, W. S. (2007), Wavelet monitoring of spatial surface roughness for plasma diagnosis, Microelectronic Engineering, 84, 2810-2816.
DOI
|
12 |
Kim, B., Kim, J., Lee, S. H., Park, J., and Lee, B. T. (2005), Plasma etching of silicon oxynitride in a low pressure C2F6 plasma, Journal of Korean Physics Society, 47, 712-715.
|
13 |
Kim, B. and Kim, W. (2007), Partial X-ray photoelectron spectroscopy to constructing neural network model of plasma etching surface, Microelectronic Engineering, 84, 584-589.
DOI
|
14 |
Kim, B. and Kwon, M. (2008), Optimization of PCAapplied in-situ spectroscopy data using neural network and genetic algorithm, Applied Spectroscopy, 62(1), 73-77.
DOI
|
15 |
Kim, B. and Park, M. (2006), Prediction of surface roughness using X-ray photoelectron spectroscopy and neural networks, Applied Spectroscopy, 60(10), 1192-1197.
DOI
|
16 |
Ko, Y.-D., Jeong, Y. S., Jeong, M. K., Garcia-Diaz, A., and Kim, B. (2010), Functional kernel-based modeling of wavelet compressed optical emission spectral data: Prediction of plasma etch process, IEEE Sensors Journal, 10(3), 746-754.
DOI
|
17 |
Kolari, K. (2008), Deep plasma etching of glass with a silicon shadow mask, Sensors and Actuators A: Physical, 141, 677-684.
DOI
|
18 |
Picard, R. W., Vyzas, E., and Healey, J. (2001), Toward machine emotional intelligence: Analysis of affective physiological state, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(10), 1175-1191.
DOI
|
19 |
Sugawara, M. (1998), Plasma etching fundamentals and applications, Oxford University Press, Oxford.
|
20 |
Rosipal, R. and Trejo, L. J. (2001), Kernel partial least squares regression in reproducing kernel Hilbert space, Journal of Machine Learning Research, 2, 97-123.
|
21 |
Zhang, G.-M., Harvey, D. M., and Braden, D. R. (2006), Resolution improvement of acoustic micro-imaging by continuous wavelet transform for semiconductor inspection, Microelectronics Reliability, 46, 811-821.
DOI
|