Neurocomputing, Volume 48

Volume 48, Number 1-4, October 2002

• Michel Verleysen, Joos Vandewalle:
  Special issue on fundamental and information processing aspects of neurocomputing. 1-2
  
• Gaetano Liborio Aiello:
  Diffusive neural network. 3-15
  
• Sander M. Bohte, Joost N. Kok, Johannes A. La Poutré:
  Error-backpropagation in temporally encoded networks of spiking neurons. 17-37
  
• Jochen J. Steil:
  Local stability of recurrent networks with time-varying weights and inputs. 39-51
  
• Zalán Heszberger, József Bíró:
  An optimization neural network model with time-dependent and lossy dynamics. 53-62
  
• Colin Campbell:
  Kernel methods: a survey of current techniques. 63-84
  
• Johan A. K. Suykens, Jos De Brabanter, Lukas Lukas, Joos Vandewalle:
  Weighted least squares support vector machines: robustness and sparse approximation. 85-105
  
• Axel Wismüller, Frank Vietze, Dominik R. Dersch, Johannes Behrends, Klaus Hahn, Helge Ritter:
  The deformable feature map - a novel neurocomputing algorithm for adaptive plasticity in pattern analysis. 107-139
  
• Ping Jiang, Rolf Unbehauen:
  Iterative learning neural network control for nonlinear system trajectory tracking. 141-153
  
• Joaquín Pizarro Junquera, Elisa Guerrero Vázquez, Pedro L. Galindo:
  Multiple comparison procedures applied to model selection. 155-173
  
• Riadh Kallel, Marie Cottrell, Vincent Vigneron:
  Bootstrap for neural model selection. 175-183
  
• Mark Girolami:
  Latent variable models for the topographic organisation of discrete and strictly positive data. 185-198
  
• Michael Dittenbach, Andreas Rauber, Dieter Merkl:
  Uncovering hierarchical structure in data using the growing hierarchical self-organizing map. 199-216
  
• Timo Kostiainen, Jouko Lampinen:
  On the generative probability density model in the self-organizing map. 217-228
  
• Thomas Villmann:
  Neural maps for faithful data modelling in medicine - state-of-the-art and exemplary applications. 229-250
  
• Romuald Boné, Michel Crucianu, Jean Pierre Asselin de Beauville:
  Learning long-term dependencies by the selective addition of time-delayed connections to recurrent neural networks. 251-266
  
• Skander Soltani:
  On the use of the wavelet decomposition for time series prediction. 267-277
  
• James McNames:
  Local averaging optimization for chaotic time series prediction. 279-297
  
• Amaury Lendasse, John Aldo Lee, Vincent Wertz, Michel Verleysen:
  Forecasting electricity consumption using nonlinear projection and self-organizing maps. 299-311
  
• Winfried A. Fellenz, John G. Taylor:
  Establishing retinotopy by lateral-inhibition type homogeneous neural fields. 313-322
  
• Francesco Panerai, Giorgio Metta, Giulio Sandini:
  Learning visual stabilization reflexes in robots with moving eyes. 323-337
  
• Jordi Solé i Casals, Christian Jutten, Anisse Taleb:
  Parametric approach to blind deconvolution of nonlinear channels. 339-355
  
• Tim W. Nattkemper, Heiko Wersing, Walter Schubert, Helge Ritter:
  A neural network architecture for automatic segmentation of fluorescence micrographs. 357-367
  
• Jiongtao Huang, Masafumi Hagiwara:
  A combined multi-winner multidirectional associative memory. 369-389
  
• Burkhard Lenze:
  On a perceptron-type learning rule for higher order Hopfield neural networks including dilation and translation. 391-401
  
• Faa-Jeng Lin, Rong-Jong Wai:
  Hybrid computed torque controlled motor-toggle servomechanism using fuzzy neural network uncertainty observer. 403-422
  
• Perambur S. Neelakanta, Apiruk Preechayasomboon:
  Development of a neuroinference engine for ADSL modem applications in telecommunications using an ANN with fast computational ability. 423-441
  
• Ashraf M. Abdelbar, Sahar Attia, Gene A. Tagliarini:
  A hybridization of Bayesian and neural learning. 443-453
  
• Dan Simon:
  Training radial basis neural networks with the extended Kalman filter. 455-475
  
• Derong Liu, Myron E. Hohil, Stanley H. Smith:
  N-bit parity neural networks: new solutions based on linear programming. 477-488
  
• Carl G. Looney:
  Radial basis functional link nets and fuzzy reasoning. 489-509
  
• Sergio Bermejo, Joan Cabestany:
  The effect of finite sample size on on-line K-means. 511-539
  
• Wei-Der Chang, Rey-Chue Hwang, Jer-Guang Hsieh:
  Stable direct adaptive neural controller of nonlinear systems based on single auto-tuning neuron. 541-554
  
• Regina Célia Coelho, Luciano da Fontoura Costa:
  Realistic neuromorphic models and their application to neural reorganization simulations. 555-571
  
• Jani J. T. Lahnajärvi, Mikko Lehtokangas, Jukka Saarinen:
  Evaluation of constructive neural networks with cascaded architectures. 573-607
  
• Iulian B. Ciocoiu:
  RBF networks training using a dual extended Kalman filter. 609-622
  
• Giorgio Valentini, Francesco Masulli:
  NEURObjects: an object-oriented library for neural network development. 623-646
  
• Martin Schäfer, Tim Schönauer, Carsten Wolff, Georg Hartmann, Heinrich Klar, Ulrich Rückert:
  Simulation of spiking neural networks -- architectures and implementations. 647-679
  
• Jinhua Xu, Daniel W. C. Ho:
  A basis selection algorithm for wavelet neural networks. 681-689
  
• P. Thangavel, T. Kathirvalavakumar:
  Training feedforward networks using simultaneous perturbation with dynamic tunneling. 691-704
  
• Ryotaro Kamimura:
  Controlling internal representations by structural information. 705-725
  
• Carlos Javier Mantas, Jose M. Mantas Ruiz, Fernando Rojas:
  A procedure for improving generalization in classification trees. 727-740
  
• Andrzej Wichert:
  Learning of associative prediction by experience. 741-762
  
• Simone Fiori:
  Blind deconvolution by simple adaptive activation function neuron. 763-778
  
• Enrico Capobianco:
  Independent component analysis and resolution pursuit with wavelet and cosine packets. 779-806
  
• Yat-Fung Yam, Chi-Tat Leung, Peter Kwong-Shun Tam, Wan-Chi Siu:
  An independent component analysis based weight initialization method for multilayer perceptrons. 807-818
  
• Victoria J. Hodge, Jim Austin:
  Hierarchical word clustering - automatic thesaurus generation. 819-846
  
• Francis Eng Hock Tay, Lijuan Cao:
  Modified support vector machines in financial time series forecasting. 847-861
  
• Yi-Chung Hu, Ruey-Shun Chen, Yen-Tseng Hsu, Gwo-Hshiung Tzeng:
  Grey self-organizing feature maps. 863-877
  
• Serge N. Demidenko, Vincenzo Piuri:
  Concurrent diagnosis in digital implementations of neural networks. 879-903
  
• Dean K. McNeill, Howard C. Card:
  Dynamic range and error tolerance of stochastic neural rate codes. 905-917
  
• Yuan Tian, Jie Zhang, Julian Morris:
  Optimal control of a fed-batch bioreactor based upon an augmented recurrent neural network model. 919-936
  
• Katsuyuki Hagiwara:
  Regularization learning, early stopping and biased estimator. 937-955
  
• Mohammad Reza Meybodi, Hamid Beigy:
  A note on learning automata-based schemes for adaptation of BP parameters. 957-974
  
• Vicente Ruiz de Angulo, Carme Torras:
  A deterministic algorithm that emulates learning with random weights. 975-1002
  
• Henry C. Tuckwell, Frederic Y. M. Wan, Roger Rodriguez:
  Analytical determination of firing times in stochastic nonlinear neural models. 1003-1007
  
• In-Cheol Kim, Sung-Il Chien:
  Speed-up of error backpropagation algorithm with class-selective relevance. 1009-1014
  
• Harold Szu, Pornchai Chanyagorn, Ivica Kopriva:
  Sparse coding blind source separation through Powerl. 1015-1020
  
• Rong Long Wang, Zheng Tang, Qi Ping Cao:
  A learning method in Hopfield neural network for combinatorial optimization problem. 1021-1024
  
• Gavin C. Cawley, Nicola L. C. Talbot:
  Improved sparse least-squares support vector machines. 1025-1031
  
• Paulo J. G. Lisboa, Terence A. Etchells, Dave C. Pountney:
  Minimal MLPs do not model the XOR logic. 1033-1037
  
• Hazem M. El-Bakry:
  Face detection using fast neural networks and image decomposition. 1039-1046
  
• Huafu Chen, Dezhong Yao, Lin Chen:
  A new method for detecting brain activities from fMRI dataset. 1047-1052
  
• M. Z. Arslanov, D. U. Ashigaliev, E. E. Ismail:
  N-bit parity ordered neural networks. 1053-1056
  
• James M. Hogan:
  Advanced mean field methods: theory and practice: M. Opper and D. Saad (Eds.); MIT Press, Cambridge, MA, 2001, 300pp. ISBN 0-262-15054-9. 1057-1060