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