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Volumn 9, Issue 5, 1996, Pages 871-879

A regularity condition of the information matrix of a multilayer perceptron network

Author keywords

Information matrix; Irreducibility; Minimality; Multilayer perceptron; Parametric estimation; Sigmoidal function

Indexed keywords

GRAPH THEORY; INFORMATION THEORY; LEARNING SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION;

EID: 0030198493     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/0893-6080(95)00119-0     Document Type: Article
Times cited : (79)

References (15)
  • 1
    • 0004199721 scopus 로고
    • New York: McGraw-Hill
    • Ahlfors, L.V. (1966). Complex analysis (pp. 101-172). New York: McGraw-Hill.
    • (1966) Complex Analysis , pp. 101-172
    • Ahlfors, L.V.1
  • 2
    • 0016355478 scopus 로고
    • A new look at the statistical model identification
    • Akaike H. A new look at the statistical model identification. IEEE Transactions on Automatic Control. 19(6):1974;716-723.
    • (1974) IEEE Transactions on Automatic Control , vol.19 , Issue.6 , pp. 716-723
    • Akaike, H.1
  • 3
    • 0003355631 scopus 로고
    • Differential-geometrical methods in statistics
    • Berlin: Springer-Verlag
    • Amari, S. (1985). Differential-geometrical methods in statistics. Lecture notes in statistics 28. Berlin: Springer-Verlag.
    • (1985) Lecture Notes in Statistics , vol.28
    • Amari, S.1
  • 4
    • 0027599793 scopus 로고
    • Universal approximation bounds for superpositions of a sigmoidal function
    • Barron A.R. Universal approximation bounds for superpositions of a sigmoidal function. IEEE Transactions on Information Theory. 39:1993;930-945.
    • (1993) IEEE Transactions on Information Theory , vol.39 , pp. 930-945
    • Barron, A.R.1
  • 5
    • 0001199897 scopus 로고
    • On the geometry of feedforward neural network error surfaces
    • Chen A.M., Liu H., Hecht-Nielsen R. On the geometry of feedforward neural network error surfaces. Neural Computation. 5:1993;910-927.
    • (1993) Neural Computation , vol.5 , pp. 910-927
    • Chen, A.M.1    Liu, H.2    Hecht-Nielsen, R.3
  • 6
    • 0003402343 scopus 로고
    • Princeton, NJ: Princeton University Press
    • Crameér, H. (1946). Mathematical method of statistics (pp.497-506). Princeton, NJ: Princeton University Press.
    • (1946) Mathematical Method of Statistics , pp. 497-506
    • Crameér, H.1
  • 7
    • 0024861871 scopus 로고
    • Approximation by superpositions of a sigmoidal function
    • Cybenco G. Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems. 2(4):1989;303-314.
    • (1989) Mathematics of Control, Signals and Systems , vol.2 , Issue.4 , pp. 303-314
    • Cybenco, G.1
  • 8
    • 0024866495 scopus 로고
    • On the approximate realization of continuous mapping by neural networks
    • Funahashi K. On the approximate realization of continuous mapping by neural networks. Neural Networks. 2:1989;183-192.
    • (1989) Neural Networks , vol.2 , pp. 183-192
    • Funahashi, K.1
  • 10
    • 0024880831 scopus 로고
    • Multi-layer feed-forward networks are universal approximators
    • Hornik K., Stinchcombe M., White H. Multi-layer feed-forward networks are universal approximators. Neural Networks. 2:1989;359-366.
    • (1989) Neural Networks , vol.2 , pp. 359-366
    • Hornik, K.1    Stinchcombe, M.2    White, H.3
  • 11
    • 0000720909 scopus 로고
    • Function equivalent feedforward neural networks
    • Kȧrková V., Kainen P.C. Function equivalent feedforward neural networks. Neural Computation. 6:1994;543-558.
    • (1994) Neural Computation , vol.6 , pp. 543-558
    • Karková, V.1    Kainen, P.C.2
  • 12
    • 0000646059 scopus 로고
    • Learning internal representations by error propagation
    • D. E., Rumelhart, J. L. McClelland, & the PDP Research Group (eds.) Cambridge, MA: MIT Press
    • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1986). Learning internal representations by error propagation. In D. E., Rumelhart, J. L. McClelland, & the PDP Research Group (eds.), Parallel distributed processing (Vol. 1, pp.318-362). Cambridge, MA: MIT Press.
    • (1986) Parallel Distributed Processing , vol.1 , pp. 318-362
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 13
    • 0026897370 scopus 로고
    • Uniqueness of the weights for minimal feed-forward nets with a given input-output map
    • Sussmann H.J. Uniqueness of the weights for minimal feed-forward nets with a given input-output map. Neural Networks. 5:1992;589-593.
    • (1992) Neural Networks , vol.5 , pp. 589-593
    • Sussmann, H.J.1
  • 14
    • 0029306567 scopus 로고
    • Probabilistic design of layered neural networks based on their unified framework
    • Watanabe S., Fukumizu K. Probabilistic design of layered neural networks based on their unified framework. IEEE Transactions on Neural Networks. 6(3):1995;691-702.
    • (1995) IEEE Transactions on Neural Networks , vol.6 , Issue.3 , pp. 691-702
    • Watanabe, S.1    Fukumizu, K.2
  • 15
    • 0000243355 scopus 로고
    • Learning in artificial neural networks: A statistical perspective
    • White H. Learning in artificial neural networks: A statistical perspective. Neural Computation. 1:1989;425-464.
    • (1989) Neural Computation , vol.1 , pp. 425-464
    • White, H.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.