Neurocomputing, Volume 57

Volume 57, March 2004

• Thomas Villmann:
  Special issue on new aspects in neurocomputing. 1-2
  
• Barbara Hammer, Alessio Micheli, Alessandro Sperduti, Marc Strickert:
  A general framework for unsupervised processing of structured data. 3-35
  
• Ying Han, Emilio Corchado, Colin Fyfe:
  Forecasting using twinned principal curves and twinned self-organising maps. 37-47
  
• John Aldo Lee, Amaury Lendasse, Michel Verleysen:
  Nonlinear projection with curvilinear distances: Isomap versus curvilinear distance analysis. 49-76
  
• James Henderson:
  Estimating probabilities for unbounded categorization problems. 77-86
  
• Mikael Bodén:
  Generalization by symbolic abstraction in cascaded recurrent networks. 87-104
  
• Gavin C. Cawley, Nicola L. C. Talbot, Robert J. Foxall, Stephen R. Dorling, Danilo P. Mandic:
  Heteroscedastic kernel ridge regression. 105-124
  
• Laurent Perrinet, Manuel Samuelides, Simon J. Thorpe:
  Sparse spike coding in an asynchronous feed-forward multi-layer neural network using matching pursuit. 125-134
  
• Udo Seiffert:
  Artificial neural networks on massively parallel computer hardware. 135-150
  
• Thomas Villmann, Beate Villmann, Volker Slowik:
  Evolutionary algorithms with neighborhood cooperativeness according to neural maps. 151-169
  
• Atsushi Imiya, Hisashi Ootani, Kazuhiko Kawamoto:
  Linear manifolds analysis: theory and algorithm. 171-187
  
• Francesco Masulli, Giorgio Valentini:
  An experimental analysis of the dependence among codeword bit errors in ECOC learning machines. 189-214
  
• Branko Ster:
  An integrated learning approach to environment modelling in mobile robot navigation. 215-238
  
• Jiann-Shing Shieh, Chi-Fong Chou, Sheng-Jean Huang, Ming-Chien Kao:
  Intracranial pressure model in intensive care unit using a simple recurrent neural network through time. 239-256
  
• Olivier Lezoray, Dominique Fournier, Hubert Cardot:
  Neural network induction graph for pattern recognition. 257-274
  
• Antony Browne, Brian D. Hudson, David C. Whitley, Martyn G. Ford, Phil D. Picton:
  Biological data mining with neural networks: implementation and application of a flexible decision tree extraction algorithm to genomic problem domains. 275-293
  
• Chen-Wen Yen, Chieh-Neng Young, Mark L. Nagurka:
  A false acceptance error controlling method for hyperspherical classifiers. 295-312
  
• Enrique Romero, Lluís Màrquez, Xavier Carreras:
  Margin maximization with feed-forward neural networks: a comparative study with SVM and AdaBoost. 313-344
  
• Roelof K. Brouwer:
  Feed-forward neural network for one-to-many mappings using fuzzy sets. 345-360
  
• Wen-Jyi Hwang, Chien-Min Ou, Rui-Chuan Lin, Wen-Wei Hu:
  Layered video transmission based on genetic programming for lossy channels. 361-372
  
• Tommy W. S. Chow, Sitao Wu:
  Cell-splitting grid: a self-creating and self-organizing neural network. 373-387
  
• Xi Min Zhang, Yan Qiu Chen, Nirwan Ansari, Yun Q. Shi:
  Mini-max initialization for function approximation. 389-409
  
• Silvio P. Sabatini, Fabio Solari, Luca Secchi:
  A continuum-field model of visual cortex stimulus-driven behaviour: emergent oscillations and coherence fields. 411-433
  
• Anping Chen, Jinde Cao, Lihong Huang:
  Exponential stability of BAM neural networks with transmission delays. 435-454
  
• Di Wang, Narendra S. Chaudhari:
  An approach for construction of Boolean neural networks based on geometrical expansion. 455-461
  
• Rong Long Wang:
  A genetic algorithm for subset sum problem. 463-468
  
• Mingjun Zhong, Huanwen Tang, Hongjun Chen, Yiyuan Tang:
  An EM algorithm for learning sparse and overcomplete representations. 469-476
  
• X. G. Wang, Z. Tang, H. Tamura, M. Ishii:
  A modified error function for the backpropagation algorithm. 477-484
  
• Jiahai Wang, Zheng Tang, Rong Long Wang:
  Maximum neural network with nonlinear self-feedback for maximum clique problem. 485-492
  
• Weixiang Liu, Nanning Zheng, Xi Li:
  Relative gradient speeding up additive updates for nonnegative matrix factorization. 493-499
  
• C. S. Rai, Yogesh Singh:
  Source distribution models for blind source separation. 501-505
  

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