An independent component analysis-based disturbance separation scheme for statistical process monitoring
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Industrial and Manufacturing Engineering,Software
Link
http://link.springer.com/content/pdf/10.1007/s10845-010-0394-3.pdf
Reference51 articles.
1. Altiok T., Melamed B. (2001) The case for modeling correlation in manufacturing systems. IIE Transactions 33: 779–791
2. Al-bazzaz H., Wang X. Z. (2004) Statistical process control charts for batch operations based on independent component analysis. Industrial and Engineering Chemistry Research 43(21): 6731–6741
3. Alwan L. C. (1992) Effects of autocorrelation on control chart performance. Communications in Statistics-Theory and Methods 21: 1025–1049
4. Alwan L. C., Roberts H. V. (1988) Time series modeling for statistical process control. Journal of Business and Economic Statistics 6: 87–95
5. Bell A. J., Sejnowski T. J. (1995) An information-maximization approach to blind separation and blind deconvolution. Neural Computation 7: 1129–1159
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