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Volumn 11, Issue 9, 1998, Pages 1571-1588

The recursive deterministic perceptron neural network

Author keywords

Classification problems; Convex hull; Decision region; Linear separability; NP completeness; Perceptron; Recursive deterministic perceptron; Transformation algorithm

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; BACKPROPAGATION; COMPUTATIONAL COMPLEXITY; CORRELATION METHODS; DECISION THEORY; FEEDFORWARD NEURAL NETWORKS; MATHEMATICAL MODELS; PATTERN RECOGNITION; SET THEORY;

EID: 0032418223     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0893-6080(98)00054-9     Document Type: Article
Times cited : (21)

References (22)
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    • Campbell, C.1    Perez Vicente, C.2
  • 4
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    • Nosing around the neighborhood: A new system structure and classification rule for recognition in partially exposed environments
    • Dasarathy B.W. Nosing around the neighborhood: a new system structure and classification rule for recognition in partially exposed environments. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2(1):1980;67-71.
    • (1980) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.2 , Issue.1 , pp. 67-71
    • Dasarathy, B.W.1
  • 6
    • 0000155950 scopus 로고
    • The cascade correlation architecture
    • In D. Touretzky (Ed.) San Mateo, CA: Morgan Kaufmann
    • Fahlman, S., & Lebiere, C. (1990). The cascade correlation architecture. In D. Touretzky (Ed.), Advances in neural information processing systems (Vol. 2, pp. 524-532). San Mateo, CA: Morgan Kaufmann .
    • (1990) Advances in Neural Information Processing Systems , vol.2 , pp. 524-532
    • Fahlman, S.1    Lebiere, C.2
  • 7
    • 0000764772 scopus 로고
    • The use of multiple measurements in taxonomic problems
    • Fisher R. A. The use of multiple measurements in taxonomic problems. Annual Eugenics. 7(II):1936;179-188.
    • (1936) Annual Eugenics , vol.7 , Issue.II , pp. 179-188
    • Fisher, R.A.1
  • 10
    • 0023843391 scopus 로고
    • Analysis of hidden units in a layered network trained to classify sonar targets
    • Gorman, & Sejnowski, T. (1988). Analysis of hidden units in a layered network trained to classify sonar targets. Neural Networks, 1(1).
    • (1988) Neural Networks , vol.1 , Issue.1
    • Gorman1    Sejnowski, T.2
  • 12
    • 0029196134 scopus 로고
    • The geometrical learning of binary neural networks
    • Kim J.H., Park S.K. The geometrical learning of binary neural networks. IEEE Transactions on Neural Networks. 6(1):1995;237-247.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , Issue.1 , pp. 237-247
    • Kim, J.H.1    Park, S.K.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.