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Volumn 283, Issue 6, 2010, Pages 854-878

Integral combinations of Heavisides

Author keywords

Feedforward neural network; Function of controlled decay; Green's function for iterated Laplacians; Heaviside function; Integral formula; Order of vanishing; Perceptron; Plane wave; Radon transform

Indexed keywords


EID: 77954163756     PISSN: 0025584X     EISSN: 15222616     Source Type: Journal    
DOI: 10.1002/mana.200710029     Document Type: Article
Times cited : (15)

References (20)
  • 1
    • 0027599793 scopus 로고
    • Universal approximation bounds for superposition of a sigmoidal function
    • A. R. Barron, Universal approximation bounds for superposition of a sigmoidal function, IEEE Trans. Inform. Theory 39, 930-945 (1993).
    • (1993) IEEE Trans. Inform. Theory , vol.39 , pp. 930-945
    • Barron, A.R.1
  • 4
    • 0024874675 scopus 로고
    • Proceedings of the IJCNN Conference, Washington, D. C., June 18-22, (IEEE Press, New York, 1989), pp. I
    • S.M. Carroll and B.W. Dickinson, Construction of neural nets using the Radon transform, in: Proceedings of the IJCNN Conference, Washington, D. C., June 18-22, 1989 (IEEE Press, New York, 1989), pp. I. 607-611.
    • (1989) Construction of neural nets using the Radon transform , pp. 607-611
    • Carroll, S.M.1    Dickinson, B.W.2
  • 8
    • 0024866495 scopus 로고
    • On the approximate realization of continuous mappings by neural networks
    • K. Funahashi, On the approximate realization of continuous mappings by neural networks, Neural Networks 2, 183-192 (1989).
    • (1989) Neural Networks , vol.2 , pp. 183-192
    • Funahashi, K.1
  • 10
    • 0003085388 scopus 로고
    • Rates of convergence for radial basis function and neural networks
    • Chapman & Hall, London
    • F. Girosi and G. Anzellotti, Rates of convergence for radial basis function and neural networks, in: Artificial Neural Networks for Speech and Vision (Chapman & Hall, London, 1993), pp. 97-113.
    • (1993) Artificial Neural Networks for Speech and Vision , pp. 97-113
    • Girosi, F.1    Anzellotti, G.2
  • 13
    • 0025799121 scopus 로고
    • Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory
    • Y. Ito, Representation of functions by superpositions of a step or sigmoid function and their applications to neural network theory, Neural Networks 4, 385-394 (1991).
    • (1991) Neural Networks , vol.4 , pp. 385-394
    • Ito, Y.1
  • 14
    • 0038009873 scopus 로고    scopus 로고
    • Best approximation by linear combinations of characteristic functions of half spaces
    • P. C. Kainen, V. Kůrková, and A. Vogt, Best approximation by linear combinations of characteristic functions of half spaces, J. Approx. Theory 122, 151-159 (2003).
    • (2003) J. Approx. Theory , vol.122 , pp. 151-159
    • Kainen, P.C.1    Kůrková, V.2    Vogt, A.3
  • 15
    • 0008241587 scopus 로고    scopus 로고
    • Geometry and topology of continuous best and near best approximations
    • P. C. Kainen, V. Kůrková, and A. Vogt, Geometry and topology of continuous best and near best approximations, J. Approx. Theory 105, 252-262 (2000).
    • (2000) J. Approx. Theory , vol.105 , pp. 252-262
    • Kainen, P.C.1    Kůrková, V.2    Vogt, A.3
  • 16
    • 18744387645 scopus 로고    scopus 로고
    • An integral formula for Heaviside neural networks
    • P. C. Kainen, V. Kůrková, and A. Vogt, An integral formula for Heaviside neural networks, Neural Network World 3, 313-319 (2000).
    • (2000) Neural Network World , vol.3 , pp. 313-319
    • Kainen, P.C.1    Kůrková, V.2    Vogt, A.3
  • 17
    • 0034266877 scopus 로고    scopus 로고
    • Best approximation by Heaviside perceptron networks
    • P. C. Kainen, V. Kůrková, and A. Vogt, Best approximation by Heaviside perceptron networks, Neural Networks 13, 695-697 (2000).
    • (2000) Neural Networks , vol.13 , pp. 695-697
    • Kainen, P.C.1    Kůrková, V.2    Vogt, A.3
  • 18
    • 0344993943 scopus 로고    scopus 로고
    • Approximation by neural networks is not continuous
    • P. C. Kainen, V. Kůrková, and A. Vogt, Approximation by neural networks is not continuous, Neurocomputing 29, 47-56 (1999).
    • (1999) Neurocomputing , vol.29 , pp. 47-56
    • Kainen, P.C.1    Kůrková, V.2    Vogt, A.3
  • 19
    • 0343118761 scopus 로고    scopus 로고
    • Estimates of the number of hidden units and variation with respect to half-spaces
    • V. Kůrková, P. C. Kainen, and V. Kreinovich, Estimates of the number of hidden units and variation with respect to half-spaces, Neural Networks 10, 1061-1068 (1997).
    • (1997) Neural Networks , vol.10 , pp. 1061-1068
    • Kůrková, V.1    Kainen, P.C.2    Kreinovich, V.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.