- CORTES , C. and VAPNIK , V. 1995 . Support vector networks . Machine Learning , 20 : 273 – 297 .
- CHAKRABORTI , S. , VAN DER LAAN , P. and BAKIR , S. T. 2001 . Nonparametric control charts: an overview and some results . Journal of Quality Technology , 3 : 304 – 315 .
- LOWRY , C. A. and MONTGOMERY , D. C. 1995 . A review of multivariate control charts . IIE Transactions , 27 : 800 – 810 .
- MACGREGOR , J. F. and KOURTI , T. 1995 . Statistical process control of multivariate processes . Control Engineering Practise , 3 : 403 – 414 .
- MONTGOMERY , D. C. 2001 . Introduction to Statistical Quality Control, , 4th edn , New York : Wiley .
- MURPHY , B. J. 1987 . Selecting out of control variables with the T multivariate quality control procedure . The Statistician , 36 : 571 – 583 .
- POLANSKY , A. M. 2001 . A smooth nonparametric approach to multivariate process capability . Technometrics , 43 : 199 – 211 .
- RAICH , A. and CINAR , A. 1996 . Statistical process monitoring and disturbance diagnosis in multivariate continuous processes . AIChE Journal , 42 : 995 – 1009 .
- SCHILLING , E. G. and NELSON , P. R. 1976 . The effect of non-normality on the control limits of X charts . Journal of Quality Technology , 8 : 183 – 188 .
- SCHÖLKOPF , B. , MIKA , S. , BURGES , C. J. C. , KNIRSCH , P. , MULLER , K.-R. , RATSCH , G. and SMOLA , A. J. 1999 . Input space versus feature space in kernel-based methods . IEEE Transactions on Neural Networks , 10 : 1000 – 1017 .
- SUN , R. X. 2000 . “ Evolutionary computation and intelligent diagnosis ” . China : Xi'an Jiaotong University, PR . PhD dissertation,
- TAX , D. M. J. , YPMA , A. and DUIN , R. P. W. Pump failure detection using support vector data description . Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis . Amsterdam, Netherlands. pp. 415 – 425 .
- TAX , D. M. J. , YPMA , A. and DUIN , R. P. W. Support vector data description applied to machine vibration analysis . Proceedings of the Fifth Annual Conference of the Advanced School for Computing and Imaging . Heijen, Netherlands. pp. 398 – 405 .
- VAPNIK , V. 1995 . The Nature of Statistical Learning Theory , New York : Springer .
- VAPNIK , V. 1998 . “ Three remarks on the support vector method of function estimation ” . In Advances in Kernel Methods: Support Vector Learning , Edited by: Schölkopf , B. , Surges , C. J. C. and Smola , A. J. Cambridge : MIT Press .
A kernel-distance-based multivariate control chart using support vector methods
Reprints and Corporate Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
To request a reprint or corporate permissions for this article, please click on the relevant link below:
Academic Permissions
Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?
Obtain permissions instantly via Rightslink by clicking on the button below:
If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.
Related research
People also read lists articles that other readers of this article have read.
Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.
Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.