Bishop CM. Neural networks for pattern recognition. New York:
Oxford University Press; 1995.
ˆ[22] Seixas JM, Caloba LP, Delpino I. Relevance criteria for variance
selection in classifier designs. In: International Conference on
Engineering Applications of Neural Networks; 1996. p. 451–4.
[23] Dong D, McAvoy TJ. Nonlinear principal component analysis-based
on principal curves and neural networks. Comput Chem Engng 1996;
20(1):65–78.
[24] Ang AHS, Tang WH. Probability concepts in engineering planning
and design. Basic principles, vol. 1. Canada: Wiley; 1975.
ˆ[25] Mery D, Silva RR, Caloba LP, Rebello JMA. Pattern recognition in the
automatic inspection of aluminium castings. Insight 2003;45(7):1 –9.
[26] Mery D, Filbert D. Classification of potential defects in the automatic
inspection of aluminium castings using statistical pattern recognition.
In: 8th European Conference on Non Destructive Testing, Barcelona;
June 17 –21, 2002. p. 1-13.
Bishop CM. Neural networks for pattern recognition. New York:
Oxford University Press; 1995.
ˆ[22] Seixas JM, Caloba LP, Delpino I. Relevance criteria for variance
selection in classifier designs. In: International Conference on
Engineering Applications of Neural Networks; 1996. p. 451–4.
[23] Dong D, McAvoy TJ. Nonlinear principal component analysis-based
on principal curves and neural networks. Comput Chem Engng 1996;
20(1):65–78.
[24] Ang AHS, Tang WH. Probability concepts in engineering planning
and design. Basic principles, vol. 1. Canada: Wiley; 1975.
ˆ[25] Mery D, Silva RR, Caloba LP, Rebello JMA. Pattern recognition in the
automatic inspection of aluminium castings. Insight 2003;45(7):1 –9.
[26] Mery D, Filbert D. Classification of potential defects in the automatic
inspection of aluminium castings using statistical pattern recognition.
In: 8th European Conference on Non Destructive Testing, Barcelona;
June 17 –21, 2002. p. 1-13.
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