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Volumn 20, Issue 3, 2005, Pages 303-307

Online learning algorithm for feedforward neural networks with moving range

Author keywords

Feedforward neural networks; Machine learning; Online learning; Statistical learning theory

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; FEEDFORWARD NEURAL NETWORKS; NEURAL NETWORKS; ROBOT LEARNING; SIGNAL FILTERING AND PREDICTION; STATISTICAL METHODS;

EID: 17644385188     PISSN: 10010920     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (2)

References (8)
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  • 3
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    • A fast new algorithm for training feedforward networks
    • Robert S Scalero, Nazif Tepedelenlioglu. A fast new algorithm for training feedforward networks[J]. IEEE Trans on Signal Processing, 1992, 40(1): 202-210.
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    • A new algorithm for improving the generalization performance and real-time ability of feedforward neural networks
    • Li D M, Wang Z O. A new algorithm for improving the generalization performance and real-time ability of feedforward neural networks[J]. Electric Machines and Control, 2002, 6(3): 241-264.
    • (2002) Electric Machines and Control , vol.6 , Issue.3 , pp. 241-264
    • Li, D.M.1    Wang, Z.O.2
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    • High speed learning algorithm for a multilayer feedforward neural network and its application
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    • (2002) Control and Decision , vol.17 , Issue.S , pp. 817-819
    • Ye, J.1    Zhang, X.H.2
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    • Gradient radial basis function networks for nonlinear and nonstationary time series prediction
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    • Chng, E.S.1    Chen, S.2    Mulgrew, B.3
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    • The relationship between kernel functions based SVM and three-layer feedforward neural networks
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    • (2002) Chinese J of Computers , vol.25 , Issue.7 , pp. 696-700
    • Zhang, L.1
  • 8
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    • Chinese source


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.