Neurocomputing, Volume 29

Volume 29, Number 1-3, November 1999

• André Elisseeff, Hélène Paugam-Moisy:
  JNN, a randomized algorithm for training multilayer networks in polynomial time. 3-24
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• Max H. Garzon, Fernanda Botelho:
  Dynamical approximation by recurrent neural networks. 25-46
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• Paul C. Kainen, Vera Kurková, Andrew Vogt:
  Approximation by neural networks is not continuous. 47-56
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• Aleksander Kolcz, Nigel M. Allinson:
  The general memory neural network and its relationship with basis function architectures. 57-84
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• Sethu Vijayakumar, Hidemitsu Ogawa:
  RKHS-based functional analysis for exact incremental learning. 85-113
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• Nageswara S. V. Rao:
  Simple sample bound for feedforward sigmoid networks with bounded weights. 115-122
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