[1] Al-Otum, H.M.(2003), Morphological operators for color image processing based on Mahalanobis
distance measure, Optical Engineering, 42 (9); 2595-2606.
[2] Anandan, P., Irani M.(2002), Factorization with uncertainty, International Journal of Computer
Vision, 49 (2-3); 101-116.
[3] Asada, M. (2001), Wafer yield prediction by the Mahalanobis-Taguchi system, IEEE International
Workshop on Statistical Methodology, 6; 25-28.
[4] Garcia-Lagos, F., Joya, G., Marin, F.J., Sandoval F. (2003), Modular power system topology
assessment using Gaussian potential functions, IEEE Proceedings-Generation Transmission and
Distribution, 150 (5); 635-640.
[5] Hayashi, S., Y. Tanaka, Kodama E. (2001), A new manufacturing control system using Mahalanobis
distance for maximizing productivity, IEEE Transactions, 15 (4); 59-62.
[6] Manly, B.F.J. (1994), Multivariate Statistical Methods: A Primer; Chapman & Hall, London.
[7] Shen, H., Carter, J.F., Brereton, R.G., Eckers C. (2003), Discrimination between tablet production
methods using pyrolysis-gas chromatography-mass spectrometry and pattern recognition, Analyst,
128(3); 287-292.
[8] Taguchi, G., Jugulum R. (2002), The Mahalanobis-Taguchi strategy; John Wiley & Sons, Inc., New
York, NY.
[9] Taguchi, S.(2000), Mahalanobis-Taguchi system, ASI Taguchi Symposium, Detroit, MI.
[10] Wu, Y. (2004), Pattern recognition using Mahalanobis distance, TPD Symposium, Journal of Quality
Engineering Forum, 12 (5); 787-795.