Neurocomputing, Volume 30

Volume 30, Number 1-4, January 2000

• Ian T. Nabney, Dan Cornford, Christopher K. I. Williams:
  Bayesian inference for wind field retrieval. 3-11
  
• Dan Cornford, Guillaume Ramage, Ian T. Nabney:
  A scatterometer neural network sensor model with input noise. 13-21
  
• David J. Evans, Dan Cornford, Ian T. Nabney:
  Structured neural network modelling of multi-valued functions for wind vector retrieval from satellite scatterometer measurements. 23-30
  
• Fouad Badran, Michel Crépon, Carlos Mejia, Sylvie Thiria, N. Tran:
  Empirical transfer function determination by the use of multilayer perceptron. 31-35
  
• P. Richaume, Fouad Badran, Michel Crépon, Carlos Mejia, H. Roquet, Sylvie Thiria:
  Neural network wind retrieval from ERS-1 scatterometer data. 37-46
  
• Christophe Ambroise, Geniève Sèze, Fouad Badran, Sylvie Thiria:
  Hierarchical clustering of self-organizing maps for cloud classification. 47-52
  
• Olivier Maas, Jean-Philippe Boulanger, Sylvie Thiria:
  Use of neural networks for predictions using time series: Illustration with the El Niño Southern oscillation phenomenon. 53-58
  
• Michel de Bollivier, Walter Eifler, Sylvie Thiria:
  Sea surface temperature forecasts using on-line local learning algorithm in upwelling regions. 59-63
  
• Fionn Murtagh, G. Zheng, J. G. Campbell, Alex Aussem:
  Neural network modelling for environmental prediction. 65-70
  
• Alex Aussem, David Hill:
  Neural-network metamodelling for the prediction of Caulerpa taxifolia development in the Mediterranean sea. 71-78
  
• Chi Chiu Cheung, Lei Xu:
  Some global and local convergence analysis on the information-theoretic independent component analysis approach. 79-102
  
• Sreeparna Banerjee, D. Dutta Majumder:
  Shape matching in multimodal medical images using point landmarks with Hopfield net. 103-116
  
• Ying Tan, Chao Deng:
  Solving for a quadratic programming with a quadratic constraint based on a neural network frame. 117-128
  
• Yonghong Tan, Mehrdad Saif:
  Neural-networks-based nonlinear dynamic modeling for automotive eng. 129-142
  
• Tianping Chen, Shun-ichi Amari:
  Dynamic behavior of the robust decorrelation process. 143-151
  
• Antanas Verikas, Adas Gelzinis:
  Training neural networks by stochastic optimisation. 153-172
  
• Lei Guo:
  Parallel double-conversion spiking neural network for world-centered recognition. 173-183
  
• Mark James Neal:
  An analog VLSI design for a neuron with a choice of learning rules. 185-200
  
• Arthur Petrosian, Danil V. Prokhorov, Richard Homan, Richard Dasheiff, Donald C. Wunsch II:
  Recurrent neural network based prediction of epileptic seizures in intra- and extracranial EEG. 201-218
  
• Jim Y. F. Yam, Tommy W. S. Chow:
  A weight initialization method for improving training speed in feedforward neural network. 219-232
  
• Jun Oh Jang, Gi Joon Jeon:
  A parallel neuro-controller for DC motors containing nonlinear friction. 233-248
  
• Daijin Kim, Sunha Ahn, Dae-Seong Kang:
  Co-adaptation of self-organizing maps by evolution and learning. 249-272
  
• Chun-Shin Lin, Chien-Kuo Li:
  A sum-of-product neural network (SOPNN). 273-291
  
• Chang-song Zhou, Tian-lun Chen:
  Chaotic neural networks and chaotic annealing. 293-300
  
• Jacek Mandziuk:
  Optimization with the Hopfield network based on correlated noises: Experimental approach. 301-321
  
• Antti Vauhkonen, Martti Juhola:
  Convergence of a spreading activation neural network with application of simulating aphasic naming errors in Finnish language. 323-332
  
• Xi Min Zhang, Yan Qiu Chen:
  Ray-guided global optimization method for training neural networks. 333-337
  
• S. Chen, Z. He, P. M. Grant:
  Artificial neural network visual model for image quality enhancement. 339-346