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Volumn 5, Issue 3, 1994, Pages 513-515

SVD-NET: An Algorithm that Automatically Selects Network Structure

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COMPLEXITY; DATA STRUCTURES; LEARNING SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; PARAMETER ESTIMATION; REDUNDANCY; STATE ESTIMATION;

EID: 0028425064     PISSN: 10459227     EISSN: 19410093     Source Type: Journal    
DOI: 10.1109/72.286929     Document Type: Article
Times cited : (37)

References (10)
  • 1
    • 0003073642 scopus 로고    scopus 로고
    • Statistical learning networks: A unifying view
    • E. J. Wegman, D. T. Gantz, and J. J. Miller, Eds. Alexandria, VA: Amer. Stat. Association
    • A. R. Barron and R. L. Barron. “Statistical learning networks: A unifying view.” Computing Science and Statistics. Proc. Twentieth Symp. on the Interface. E. J. Wegman, D. T. Gantz, and J. J. Miller, Eds. Alexandria, VA: Amer. Stat. Association, pp. 192-203.
    • Computing Science and Statistics. Proc. Twentieth Symp. on the Interface , pp. 192-203
    • Barron, A.R.1    Barron, R.L.2
  • 2
    • 0026853333 scopus 로고
    • PLS/neural networks
    • T. R. Holcomb and M. Morari, “PLS/neural networks,” Comp. Chem. Eng., vol. 16, pp. 393-411, 1992.
    • (1992) Comp. Chem. Eng. , vol.16 , pp. 393-411
    • Holcomb, T.R.1    Morari, M.2
  • 3
    • 0026853320 scopus 로고
    • Nonlinear PLS modeling using neural networks
    • S. J. Qin and T. J. McAvoy, “Nonlinear PLS modeling using neural networks.” Comp. Chem. Eng., vol. 16. pp. 379-391, 1992.
    • (1992) Comp. Chem. Eng. , vol.16 , pp. 379-391
    • Qin, S.J.1    McAvoy, T.J.2
  • 6
    • 0025403609 scopus 로고
    • Improvement of the backpropagation algorithm for training neural networks
    • J. Leonard and M. A. Kramer. “Improvement of the backpropagation algorithm for training neural networks.” Comp. Chem. Eng., vol. 14. pp. 337-341. 1990.
    • (1990) Comp. Chem. Eng. , vol.14 , pp. 337-341
    • Leonard, J.1    Kramer, M.A.2
  • 7
    • 0023952731 scopus 로고
    • The use of biased least-squares estimates for parameters in discrete-time pulse response models
    • N. L. Ricker, “The use of biased least-squares estimates for parameters in discrete-time pulse response models,” Ind. Eng. Chem. Res., vol. 27, pp. 343-350, 1988.
    • (1988) Ind. Eng. Chem. Res. , vol.27 , pp. 343-350
    • Ricker, N.L.1
  • 8
    • 0026403834 scopus 로고
    • Direct and indirect model-based control using artificial neural networks
    • D. C. Psichogios and L. H. Ungar, “Direct and indirect model-based control using artificial neural networks,” Ind. Eng. Chem. Res., vol. 30, pp. 2564-2573, 1991.
    • (1991) Ind. Eng. Chem. Res. , vol.30 , pp. 2564-2573
    • Psichogios, D.C.1    Ungar, L.H.2
  • 9
    • 0000900876 scopus 로고
    • Skeletonization: A technique for trimming the fat from a network via relevance assessment
    • D. S. Tourestzky. Ed. San Mateo, CA: Morgan Kaufmann
    • M. C. Mozer and P. Smolensky. “Skeletonization: A technique for trimming the fat from a network via relevance assessment,” in Advances in Neural Information Processing. D. S. Tourestzky. Ed. San Mateo, CA: Morgan Kaufmann, 1989.
    • (1989) Advances in Neural Information Processing
    • Mozer, M.C.1    Smolensky, P.2
  • 10
    • 0025447562 scopus 로고
    • A simple procedure for pruning backpropagation trained neural networks
    • E. D. Karnin, “A simple procedure for pruning backpropagation trained neural networks,” IEEE Trans, on Neural Networks, vol. 1, pp. 239-242. 1990.
    • (1990) IEEE Trans, on Neural Networks , vol.1 , pp. 239-242
    • Karnin, E.D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.