Table of Contents

• Efficient formation of a basis in a kernel induced feature spaceGavin C. Cawley, Nicola L. C. Talbot. 1-6
• Theoretical properties of functional Multi Layer PerceptronsFabrice Rossi, Brieuc Conan-Guez, François Fleuret. 7-12
• Storing many-to-many mappings on a feed-forward neural network using fuzzy setsRoelof K. Brouwer. 13-18
• Heteroscedastic regularised kernel regression for prediction of episodes of poor air qualityRobert J. Foxall, Gavin C. Cawley, Nicola L. C. Talbot, Stephen R. Dorling, Danilo P. Mandic. 19-24
• Exploratory Data Analysis in Medicine and BioinformaticsAxel Wismüller, Thomas Villmann. 25-38
• A data visualisation method for investigating the reliability of a high-dimensional low-back-pain MLP networkMarylin L. Vaughn, Stewart J. Taylor, Michael A. Foy, Anthony J. B. Fogg. 39-44
• Double self-organizing maps to cluster gene expression dataDali Wang, Habtom W. Ressom, Mohamad T. Musavi, Christian Domnisoru. 45-50
• Improving robustness of fuzzy gene modelingRobert Reynolds, Habtom W. Ressom, Mohamad T. Musavi, Christian Domnisoru. 51-56
• Parametric bootstrap for asymptotic test of contrast difference in neural networksRiadh Kallel, Joseph Rynkiewicz. 57-64
• A resampling and multiple testing-based procedure for determining the size of a neural networkAndrés Yáñez Escolano, Elisa Guerrero Vázquez, Pedro Galindo Riaño, Joaquín Pizarro Junquera. 65-70
• Neural networks for modelling memory : case studiesHélène Paugam-Moisy, Didier Puzenat, Emanuelle Reynaud, Jean-Philippe Magué. 71-82
• Connectionist models investigating representations formed in the sequential generation of charactersFiona M. Richardson, Neil Davey, Lorna Peters, D. John Done, Sue H. Anthony. 83-88
• The problem of adaptive control in a living system or how to acquire an inverse model without the help of an external teacherKarl Theodor Kalveram, Thomas Schinauer. 89-94
• Biologically-inspired human motion detectionVijay Laxmi, John N. Carter, Robert I. Damper. 95-100
• Why will rat s go where rats will not?Jenny Hayes, Victoria Murphy, Neil Davey, Pam Smith, Lorna Peters. 101-106
• Rule extraction from support vector machinesHaydemar Núñez, Cecilio Angulo, Andreu Català. 107-112
• Fuzzy support vector machines for multiclass problemsShigeo Abe, Takuya Inoue. 113-118
• Different criteria for active learning in neural networks: a comparative studyJan Poland, Andreas Zell. 119-124
• Supervised learning in committee machines by PCAChristoph Bunzmann, Michael Biehl, Robert Urbanczik. 125-130
• The use of LS-SVM in the classification of brain tumors based on Magnetic Resonance Spectroscopy signalsLukas Lukas, Andy Devos, Johan A. K. Suykens, Leentje Vanhamme, Sabine Van Huffel, Anne Rosemary Tate, Carles Majós, Carles Arús. 131-136
• Clustering in data space and feature spaceDonald MacDonald, Colin Fyfe. 137-142
• Maximum likelihood Hebbian rulesColin Fyfe, Emilio Corchado. 143-148
• Fast exact leave-one-out cross-validation of least-squares Support Vector MachinesKamel Saadi, Gavin C. Cawley, Nicola L. C. Talbot. 149-154
• Noise derived information criterion for model selectionJoaquín Pizarro Junquera, Pedro L. Galindo, Elisa Guerrero Vázquez, Andrés Yáñez Escolano. 155-160
• An unified framework for All data at once multi-class Support Vector MachinesCecilio Angulo, Xavier Parra, Andreu Català. 161-166
• Prediction of mental development of preterm newborns at birth time using LS-SVMLieveke Ameye, Chuan Lu, Lukas Lukas, Jos De Brabanter, Johan A. K. Suykens, Sabine Van Huffel, Hans Daniels, Gunnar Naulaers, Hugo Devlieger. 167-172
• Searching for the embedded manifolds in high-dimensional data, problems and unsolved questionsJeanny Hérault, Anne Guérin-Dugué, Pierre Villemain. 173-184
• Curvilinear Distance Analysis versus IsomapJohn Aldo Lee, Amaury Lendasse, Michel Verleysen. 185-192
• Fast nonlinear dimensionality reduction with topology representing networksJakob J. Verbeek, Nikos A. Vlassis, Ben J. A. Kröse. 193-198
• When does geodesic distance recover the true hidden parametrization of families of articulated images?David L. Donoho, Carrie Grimes. 199-204
• How to generalize geometric ICA to higher dimensionsFabian J. Theis, Elmar Wolfgang Lang. 205-210
• Neural dimensionality reduction for document processingMathieu Delichère, Daniel Memmi. 211-216
• Geometric overcomplete ICAFabian J. Theis, Elmar Wolfgang Lang. 217-222
• Advantages and drawbacks of the Batch Kohonen algorithmJean-Claude Fort, Patrick Letrémy, Marie Cottrell. 223-230
• Mobile radio access network monitoring using the self-organizing mapPasi Lehtimäki, Kimmo Raivio, Olli Simula. 231-236
• Evaluating the impact of multiplicative input perturbations on radial basis function networksJosé Luis Bernier, Jesús González, Antonio Cañas, Antonio F. Díaz, F. J. Fernández, Julio Ortega. 237-244
• Learning sparse representations of three-dimensional objectsGabriele Peters, Christoph von der Malsburg. 245-250
• An estimation model of pupil size for Blink Artifact and it s applicationsMinoru Nakayama, Yasutaka Shimizu. 251-256
• Novelty detection for strain-gauge degradation using maximally correlated componentsGarry Hollier, Jim Austin. 257-262
• Modeling efficient conjunction detection with spiking neural networksSander M. Bohte, Joost N. Kok, Johannes A. La Poutré. 263-268
• Segmental duration control by time delay neural networks with asymmetric causal and retro-causal information flowsCaglayan Erden, Hans-Georg Zimmermann. 269-274
• Neural predictive coding for speech discriminant feature extraction: The DFE-NPCMohamed Chetouani, Bruno Gas, Jean-Luc Zarader, Cyril Chavy. 275-280
• Multiresolution codes for scene categorizationNathalie Denquive, Philippe Tarroux. 281-287
• Evaluation of gradient descent learning algorithms with adaptive and local learning rate for recognising hand-written numeralsMatteo Giudici, Filippo Queirolo, Maurizio Valle. 289-294
• Batch-RLVQBarbara Hammer, Thomas Villmann. 295-300
• Combining gestural and contact information for visual guidance of multi-finger graspsGunther Heidemann, Helge Ritter. 301-306
• Separation of a mixture of signals using linear filtering and second order statisticsAna Maria Tomé. 307-312
• Sparse image coding using an asynchronous spiking neural networkLaurent Perrinet, Manuel Samuelides. 313-318
• Artificial Neural Networks on Massively Parallel Computer HardwareUdo Seiffert. 319-330
• PCNN neurocomputers - Event driven and parallel architecturesCyprian Grassmann, Tim Schönauer, Carsten Wolff. 331-336
• A reconfigurable SOM hardware acceleratorMario Porrmann, Marc Franzmeier, Heiko Kalte, Ulf Witkowski, Ulrich Rückert. 337-342
• Stochastic resonance and finite resolutions in a leaky integrate-and-fire neuronNhamo Mtetwa, Leslie S. Smith, Amir Hussain. 343-348
• Hardware solutions for implementation of neural networks in High Energy Physics triggersJean-Christophe Prévotet, Bruce Denby, Patrick Garda, Bertrand Granado, Christian Kiesling. 349-356
• Perspectives on learning with recurrent neural networksBarbara Hammer, Jochen J. Steil. 357-368
• DEKF-LSTMFelix A. Gers, Juan Antonio Pérez-Ortiz, Douglas Eck, Jürgen Schmidhuber. 369-376
• Generalization by structural properties from sparse nested symbolic dataMikael Bodén. 377-382
• Estimating probabilities for unbounded categorization problemsJames Henderson. 383-388
• A general framework for unsupervised processing of structured dataBarbara Hammer, Alessio Micheli, Alessandro Sperduti. 389-394
• Undershooting: modeling dynamical systems by time grid refinementsHans-Georg Zimmermann, Ralph Neuneier, Ralph Grothmann. 395-400
• Learning in a chaotic neural networkNigel Crook, Tjeerd Olde Scheper. 401-406
• Yield curve forecasting by error correction neural networks and partial learningHans-Georg Zimmermann, Christoph Tietz, Ralph Grothmann. 407-412
• State reconstruction of piecewise linear maps using a clustering machineGilles Millerioux, Gérard Bloch. 413-418
• Unsupervised classifier for monitoring and diagnostic of time seriesStéphane Lecoeuche. 419-424
• Width optimization of the Gaussian kernels in Radial Basis Function NetworksNabil Benoudjit, Cédric Archambeau, Amaury Lendasse, John Aldo Lee, Michel Verleysen. 425-432
• High frequency forecasting with associative memoriesAndy Pasley, Jim Austin. 433-438
• Nonlinear PCA: a new hierarchical approachMatthias Scholz, Ricardo Vigário. 439-444
• Probabilistic derivation and Multiple Canonical Correlation AnalysisPei Ling Lai. 445-452
• Orthogonal transformations for optimal time series predictionMoisés Salmerón, Alberto Prieto, Julio Ortega, Carlos García Puntonet, Manuel Rodríguez Álvarez. 453-458
• Neuro-fuzzy methodologies for the clustering and the reliability estimation of olive fruit fly infestationElena Bellei, Ruggero Petacchi, Leonardo Maria Reyneri. 459-464
• Use of artificial neural networks process analyzers: a case studyHussain N. Al-Duwaish, Lahouri Ghouti, Talal O. Halawani, Mohamed Mohandes. 465-470
• Forecasting using twinned principal curvesYing Han, Colin Fyfe. 471-476
• Kernel Temporal Component AnalysisDominique Martinez, Alistair Bray. 477-482
• Exploratory Correlation AnalysisJos Koetsier, Donald MacDonald, Darryl Charles, Colin Fyfe. 483-488
• Neural networks for fault diagnosis and identification of industrial processesSilvio Simani, Cesare Fantuzzi. 489-494
• Neural networks for fault diagnosis of industrial plants at different working pointsSilvio Simani, Ronald J. Patton. 495-500
• Fault diagnosis of an electro-pneumatic valve actuator using neural networks with fuzzy capabilitiesFaisel J. Uppal, Ronald J. Patton. 501-506
• Non-linear Canonical Correlation Analysis using a RBF networksSukhbinder Kumar, Elaine B. Martin, A. Julian Morris. 507-512
• Free-swinging and locked joint fault detection and isolation in cooperative manipulatorsRenato Tinós, Marco H. Terra. 513-518