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Volumn 13, Issue 2, 2004, Pages 95-122

Incremental learning in terms of output attributes

Author keywords

Incremental learning; Neural networks; Output attributes; Supervised learning

Indexed keywords

KNOWLEDGE ACQUISITION; KNOWLEDGE REPRESENTATION; LEARNING ALGORITHMS; MULTILAYER NEURAL NETWORKS; PROBLEM SOLVING;

EID: 3242774399     PISSN: 03341860     EISSN: None     Source Type: Journal    
DOI: 10.1515/JISYS.2004.13.2.95     Document Type: Article
Times cited : (11)

References (13)
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    • Bartfai, G.1
  • 3
    • 0026453958 scopus 로고
    • Training a 3-node neural network is NP-complete
    • Blum, A., Rivest, R. L. 1992. Training a 3-node neural network is NP-complete, Neural Networks, 5, 117-128.
    • (1992) Neural Networks , vol.5 , pp. 117-128
    • Blum, A.1    Rivest, R.L.2
  • 4
    • 0033237157 scopus 로고    scopus 로고
    • An incremental-learning neural network for the classification of remote-sensing images
    • Bruzzon, L., Fernandez, P.D. 1999. An incremental-learning neural network for the classification of remote-sensing images, Pattern Recognition Letters, 20, 1241-1248.
    • (1999) Pattern Recognition Letters , vol.20 , pp. 1241-1248
    • Bruzzon, L.1    Fernandez, P.D.2
  • 6
    • 0035576171 scopus 로고    scopus 로고
    • Incremental learning with respect to new incoming input attributes
    • Guan, Sheng-Uei, Li, S. 2001. Incremental learning with respect to new incoming input attributes, Neural Processing Letters, 14, 241-260.
    • (2001) Neural Processing Letters , vol.14 , pp. 241-260
    • Guan, S.-U.1    Li, S.2
  • 7
    • 0036565572 scopus 로고    scopus 로고
    • Parallel growing and training of neural networks using output parallelism
    • Guan, Sheng-Uei, Li, S. 2002. Parallel growing and training of neural networks using output parallelism, IEEE Transactions on Neural Networks, 13, 1-9.
    • (2002) IEEE Transactions on Neural Networks , vol.13 , pp. 1-9
    • Guan, S.-U.1    Li, S.2
  • 8
    • 0003413187 scopus 로고    scopus 로고
    • Upper Saddle River, New Jersey, USA, Prentice Hall
    • nd Edition, Upper Saddle River, New Jersey, USA, Prentice Hall, 213-214.
    • (1999) nd Edition , pp. 213-214
    • Haykin, S.1
  • 11
    • 0004042460 scopus 로고
    • Proben1: A set of neural network benchmark problems and benchmarking rules
    • Department of Informatics, University of Karlsruhe, Germany
    • Prechelt, L. 1994. PROBEN1: a set of neural network benchmark problems and benchmarking rules, Technical Report 21/94, Department of Informatics, University of Karlsruhe, Germany.
    • (1994) Technical Report , vol.21 , Issue.94
    • Prechelt, L.1
  • 13
    • 0034944415 scopus 로고    scopus 로고
    • Incremental self-growing neural networks with changing environment
    • Su, Li, Guan, Sheng-Uei, Yeo, Y.C. 2001. Incremental self-growing neural networks with changing environment, Journal of Intelligent Systems, 11, 43-74.
    • (2001) Journal of Intelligent Systems , vol.11 , pp. 43-74
    • Su, L.1    Guan, S.-U.2    Yeo, Y.C.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.