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Volumn 13, Issue 2, 2002, Pages 274-282

On the geometric convergence of neural approximations

Author keywords

Feedforward neural networks; Greedy approximation; Rate of approximation; Universal approximation

Indexed keywords

APPROXIMATION THEORY; CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; ITERATIVE METHODS; THEOREM PROVING;

EID: 0036505609     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/72.991414     Document Type: Article
Times cited : (19)

References (13)
  • 4
  • 5
    • 0000796112 scopus 로고
    • A simple lemma on greedy approximations in Hilbert space and convergence rates for projection pursuit regression and neural network training
    • Mar.
    • (1992) Ann. Statist. , vol.20 , pp. 608-613
    • Jones, L.K.1
  • 9
    • 0001929506 scopus 로고
    • Finite mapping by neural networks and troth functions
    • (1992) Math. Sci. , vol.17 , pp. 69-77
    • Ito, Y.1
  • 12
    • 0030198795 scopus 로고    scopus 로고
    • A numerical implementation of Kolmogorov's superpositions
    • (1996) Neural Networks , vol.9 , Issue.5 , pp. 765-772
  • 13
    • 0031127917 scopus 로고    scopus 로고
    • A numerical implementation of Kolmogorov's superpositions II
    • (1997) Neural Networks , vol.10 , Issue.3 , pp. 447-457


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.