Table of Contents

• What are the main factors involved in the design of a Radial Basis Function Network?Ignacio Rojas Ruiz, Mancia Anguita, Eduardo Ros Vidal, Héctor Pomares, Olga Valenzuela, Alberto Prieto. 1-6 [doi]
• A supervised radial basis function neural networkShengqing Wu, Christian Van den Broeck. 7-12 [doi]
• A comparison between weighted radial basis functions and wavelet networksMirko Sgarbi, Valentina Colla, Leonardo Maria Reyneri. 13-20 [doi]
• An incremental local radial basis function networkAnna Esposito, Maria Marinaro, Silvia Scarpetta. 21-26 [doi]
• A Tikhonov approach to calculate regularisation matricesCecilio Angulo, Andreu Català. 27-32 [doi]
• Analyses on the temporal patterns of spikes of auditory neurons by a neural network and tree-based modelsTetsuya Takahashi. 33-38 [doi]
• Output jitter diverges to infinity, converges to zero or remains constantJianfeng Feng, Brunello Tirozzi, David Brown. 39-48 [doi]
• Wavelet interpolation networksChristophe P. Bernard, Stéphane Mallat, Jean-Jacques E. Slotine. 49-52 [doi]
• Generating arbitrary rhythmic patterns with purely inhibitory neural networksZhijun Yang, Felipe Maia Galvão França. 53-58 [doi]
• Brain-like intelligent control: from neural nets to larger-scale systemsPaul J. Werbos. 59-66 [doi]
• Control of a subsonic electropneumatic acoustic generator with dynamic recurrent neural networksJean-Philippe Draye, Laurent Blondel, Guy Cheron. 67-72 [doi]
• Lazy learning for control designGianluca Bontempi, Mauro Birattari, Hugues Bersini. 73-78 [doi]
• Neural networks for the solution of information-distributed optimal control problemsMarco Baglietto, Thomas Parisini, Riccardo Zoppoli. 79-84 [doi]
• Parsimonious learning feed-forward controlTheo J. A. de Vries, Lars J. Idema, Wubbe J. R. Velthuis. 85-90 [doi]
• Fast orienting movements to visual targets: neural field model of dynamic gaze controlAndreas Schierwagen, Herrad Werner. 91-98 [doi]
• Improved generalization ability of neurocontrollers by imposing NLq stability constraintsJohan A. K. Suykens, Joos Vandewalle. 99-104 [doi]
• A RNN based control architecture for generating periodic action sequencesThorsten Kolb, Winfried Ilg, Jörg Wille. 105-110 [doi]
• NAR time-series prediction: a Bayesian framework and an experimentMichel Crucianu, Crucianu Uhry, Jean Pierre Asselin de Beauville, Romuald Boné. 111-116 [doi]
• Application of a neural net in classification and knowledge discoveryKristina Schädler, Fritz Wysotzki. 117-122 [doi]
• Extending the CMAC model: adaptive input quantizationGrzegorz Piotr Klebus. 123-128 [doi]
• One or two hidden layers perceptronsMercedes Fernández, Carlos Hernández-Espinosa. 129-134 [doi]
• On the error function of interval arithmetic backpropagationMercedes Fernández, Carlos Hernández-Espinosa. 135-140 [doi]
• A neural network for the identification of the dynamic behaviour of a wheelchairLuciano Boquete, Rafael Barea, Manuel Mazo, I. Aranda. 141-148 [doi]
• What is observable in a class of neurodynamics?Jianfeng Feng, David Brown. 149-154 [doi]
• Polyhedral mixture of linear experts for many-to-one mapping inversionAmir Karniel, Ron Meir, Gideon F. Inbar. 155-160 [doi]
• On-off intermittency in small neural networks with synaptic noiseAndrzej Krawiecki, Robert A. Kosinski. 161-166 [doi]
• Recurrent SOM with local linear models in time series predictionTimo Koskela, Markus Varsta, Jukka Heikkonen, Kimmo Kaski. 167-172 [doi]
• Self-organization and convergence of the one-dimensional Kohonen algorithmAli A. Sadeghi. 173-178 [doi]
• Finding structure in text archivesAndreas Rauber, Dieter Merkl. 179-184 [doi]
• Methods for interpreting a self-organized map in data analysisSamuel Kaski, Janne Nikkilä, Teuvo Kohonen. 185-190 [doi]
• Magnification control in neural mapsThomas Villmann, J. Michael Herrmann. 191-196 [doi]
• Self-organizing ANNs for planetary surface composition researchErzsébet Merényi. 197-202 [doi]
• A new dynamic LVQ-based classifier and its application to handwritten character recognitionSergio Bermejo, Joan Cabestany, Magdalena Payeras-Capellà. 203-208 [doi]
• The self-organising map, robustness, self-organising criticality and power lawJohn A. Flanagan. 209-214 [doi]
• Invariant feature maps for analysis of orientations in image dataStephen McGlinchey, Colin Fyfe. 215-220 [doi]
• Forecasting time-series by Kohonen classificationAmaury Lendasse, Michel Verleysen, Eric de Bodt, Marie Cottrell, Philippe Grégoire. 221-226 [doi]
• Introduction to speech recognition using neural networksChristian Wellekens. 227-236 [doi]
• Self-organization in mixture densities of HMM based speech recognitionMikko Kurimo. 227-236 [doi]
• Speech recognition with a new hybrid architecture combining neural networks and continuous HMMDaniel Willett, Gerhard Rigoll. 243-248 [doi]
• Hierarchies of neural networks for connectionist speech recognitionJürgen Fritsch, Alex Waibel. 249-254 [doi]
• Training a sigmoidal network is difficultBarbara Hammer. 255-260 [doi]
• Weight saliency regularization in augmented networksPeter J. Edwards, Alan F. Murray. 261-266 [doi]
• To stop learning using the evidenceDomenico Perrotta. 267-272 [doi]
• Selecting among candidate basis functions by crosscorrelationsAndreas Poncet, Armin Deiss, Schmuel Holles. 273-278 [doi]
• A multistage on-line learning rule for multilayer neural networkPhilippe Thomas, Gérard Bloch, Claude Humbert. 279-284 [doi]
• Parameter-estimation-based learning for feedforward neural networks: convergence and robustness analysisAngelo Alessandri, Manfredi Maggiore, Marcello Sanguineti. 285-290 [doi]
• The CNN computer - a tutorialTamás Roska. 291-296 [doi]
• On the robust design of uncoupled CNNsBahram Mirzai, Drahoslav Lim, George S. Moschyts. 297-302 [doi]
• To stop learning using the evidenceYves Moreau, Joos Vandewalle. 303-308 [doi]
• Cellular neural networks: from chaos generation to compexity modellingPaolo Arena, Luigi Fortuna. 309-314 [doi]
• Ultrasound medical image processing using cellular neural networksIgor N. Aizenberg, Naum N. Aizenberg, Eugene S. Gotko, Joos Vandewalle. 315-320 [doi]
• Separation of sources in a class of post-nonlinear mixturesCarlos García Puntonet, Manuel Rodríguez Álvarez, Alberto Prieto, Beatriz Prieto. 321-326 [doi]
• Improving neural network estimation in presence of non i.i.d. noiseShahram Hosseini, Christian Jutten. 327-332 [doi]
• A self-organising neural network for modelling cortical developmentMichael W. Spratling, Gillian Hayes. 333-338 [doi]
• Learning sensory-motor cortical mappings without trainingMichael W. Spratling, Gillian Hayes. 339-344 [doi]
• Perception and action selection by anticipation of sensorimotor consequencesTorsten Seiler, Volker Stephan, Horst-Michael Gross. 345-350 [doi]
• Neural networks for financial forecastG. Rotundo, Brunello Tirozzi, M. Valente. 351-356 [doi]
• A neural approach to a sensor fusion problemValentina Colla, Mirko Sgarbi, Leonardo Maria Reyneri, Angelo M. Sabatini. 357-362 [doi]
• Canonical correlation analysis using artificial neural networksPei Ling Lai, Colin Fyfe. 363-368 [doi]
• ANN for facial information processing: a review of recent approachesBogdan Raducanu, Manuel Graña, Alicia D Anjou, F. Xabier Albizuri. 369-376 [doi]
• Hybrid Hidden Markow model / neural network models for speechreadingAlexandrina Rogozan, Paul Deléglise. 377-382 [doi]
• Face recognition: pre-processing techniques for linear autoassociatorsE. Drege, Fan Yang, Michel Paindavoine, Hervé Abdi. 383-388 [doi]
• Facial image retrieval using sequential classifiersSrinivas Gutta, Harry Wechsler. 389-394 [doi]
• Grouping complex face parts by nonlinear oscillationsSouichi Oka, Miki Kitabata, Yoshiaki Ajioka, Yoshiyasu Takefuji. 395-400 [doi]
• On a Hopfield net arising in the modelling and control of over-saturated signalized intersectionsFatine Maghrebi. 401-406 [doi]
• Construction of an interactive and competitive artificial neural network for the solution of path planning problemsE. Mulder, H. A. K. Mastebroeck. 407-412 [doi]
• Learning associative mappings from few examplesJörg A. Walter. 413-418 [doi]