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Volumn 15, Issue 10, 2003, Pages 2457-2481

On the partitioning capabilities of feedforward neural networks with sigmoid nodes

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; ARTIFICIAL NEURAL NETWORK; BIOLOGICAL MODEL; MATHEMATICS;

EID: 0041360336     PISSN: 08997667     EISSN: None     Source Type: Journal    
DOI: 10.1162/089976603322362437     Document Type: Article
Times cited : (2)

References (22)
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    • Chen, T.1    Chen, H.2
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    • Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems
    • Chen, T., & Chen, H. (1995b). Universal approximation to nonlinear operators by neural networks with arbitrary activation functions and its application to dynamical systems. IEEE Transactions on Neural Networks, 6(4), 911-917.
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    • Chen, T.1    Chen, H.2
  • 5
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    • Gibson, G.J.1    Cowan, C.F.N.2
  • 7
    • 0024880831 scopus 로고
    • Multilayer feedforward networks are universal approximators
    • Hornik, K., Stinchcombe, M., & White, H. (1989). Multilayer feedforward networks are universal approximators. Neural Networks, 2(5), 359-366.
    • (1989) Neural Networks , vol.2 , Issue.5 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 8
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    • Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory
    • Ito, Y. (1991). Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory. Neural Networks, 4(3), 385-394.
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    • Ito, Y.1
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    • errata in Vol. 21, no. 1, p. 123, 2002
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.