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Volumn 4, Issue , 2005, Pages 2308-2312

Bayesian neural networks for nonlinear multivariate manufacturing process monitoring

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NEURAL NETWORKS; MULTIVARIATE MEASUREMENT VARIABLES; OVERFITTING PROBLEMS; PARAMETER LEARNING;

EID: 33750132398     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IJCNN.2005.1556261     Document Type: Conference Paper
Times cited : (5)

References (15)
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  • 5
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    • Dong, D.1    McAvoy, T.J.2
  • 8
    • 84898960224 scopus 로고    scopus 로고
    • A polygonal line algorithm for constructing principal curves
    • B. Kégl et al., "A Polygonal Line Algorithm for Constructing Principal Curves," Proc. Neural Information Processing System, 1999.
    • (1999) Proc. Neural Information Processing System
    • Kégl, B.1
  • 9
    • 0026113980 scopus 로고
    • Nonlinear principal component analysis using associative NN
    • M.A. Kramer, "Nonlinear Principal Component Analysis using Associative NN," AIChE Journal, vol.37, pp. 233-243, 1991.
    • (1991) AIChE Journal , vol.37 , pp. 233-243
    • Kramer, M.A.1
  • 10
    • 0026954958 scopus 로고
    • Principal components, minor components and linear neural networks
    • E. Oja, "Principal Components, Minor Components and Linear Neural Networks," Neural Networks, vol.5, pp. 927-935, 1992.
    • (1992) Neural Networks , vol.5 , pp. 927-935
    • Oja, E.1
  • 11
    • 33750142876 scopus 로고    scopus 로고
    • Bayesian techniques for neural networks - Review and case studies
    • M. Gabbouj and P. Kuosmanen, editors, Finland
    • J. Lampinen and A. Vehtari, "Bayesian techniques for neural networks - review and case studies," In M. Gabbouj and P. Kuosmanen, editors, Proceedings of Eusipco'2000, X European Signal Processing Conference, vol. 2, pp. 713-720, Finland, 2000.
    • (2000) Proceedings of Eusipco'2000, X European Signal Processing Conference , vol.2 , pp. 713-720
    • Lampinen, J.1    Vehtari, A.2
  • 12
    • 0002704818 scopus 로고
    • A practical bayesian framework for backpropagation networks
    • D.C. MacKay, "A Practical Bayesian Framework for Backpropagation Networks," Neural Computation, vol. 4, pp. 448-472, 1992.
    • (1992) Neural Computation , vol.4 , pp. 448-472
    • MacKay, D.C.1
  • 14
    • 0003301456 scopus 로고    scopus 로고
    • Bayesian learning for neural networks
    • Springer-Verlag
    • R.M. Neal, "Bayesian Learning for Neural Networks," Lecture Notes in Statistics vol. 118, Springer-Verlag, 1996.
    • (1996) Lecture Notes in Statistics , vol.118
    • Neal, R.M.1
  • 15
    • 22944434926 scopus 로고    scopus 로고
    • A bayesian approach to blind source separation
    • D.B Rowe, "A Bayesian Approach to Blind Source Separation," Journal of Interdisciplinary Mathematics, vol. 5, pp. 49-76, 2002.
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    • Rowe, D.B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.