ESANN 2001: Bruges, Belgium

Pattern recognition - classification

• Andreas Alexander Albrecht, Martin J. Loomes, Kathleen Steinhöfel, Matthias Taupitz, Chak-Kuen Wong:
  A local search method for pattern classification. 1-6
  
• Chellu Chandra Sekhar, Kazuya Takeda, Fumitada Itakura:
  Recognition of consonant-vowel utterances using Support Vector Machines. 7-12
  
• Tony Van Gestel, Johan A. K. Suykens, Bart De Moor, Joos Vandewalle:
  Automatic relevance determination for Least Squares Support Vector Machines classifiers. 13-18
  

Signal processing and vision

• Axel Wismüller, Oliver Lange, Dominik R. Dersch, Klaus Hahn, Gerda L. Leinsinger:
  Analysis of dynamic perfusion MRI data by neural networks. 19-24
  
• Bogdan Raducanu, Manuel Graña:
  Visual self-localization with morphological neural networks. 25-30
  
• Carlos García Puntonet, Ali Mansour, Manuel Rodríguez Álvarez, Beatriz Prieto, Ignacio Rojas Ruiz:
  A stochastic and competitive network for the separation of sources. 31-38
  
• Vincent Vigneron, Ludovic Aubry:
  More on stationnary points in Independent Component Analysis. 39-44
  

Dedicated hardware implementations: prespectives on systems and applications

• Davide Anguita, Maurizio Valle:
  Perspectives on dedicated hardware implementations. 45-56
  
• Ángel Rodríguez-Vázquez, Servando Espejo-Meana, Rafael Domínguez-Castro, Ricardo Carmona-Galán, Gustavo Liñán:
  CMOS design of focal plane programmable array processors. 57-62
  
• Patrice Fleury, Robin Woodburn, Alan F. Murray:
  Matching analogue hardware with applications using the Products of Experts algorithm. 63-68
  
• Jordi Cosp, Jordi Madrenas:
  A microelectronic implementation of a bioinspired analog matrix for object segmentation of a visual scene. 69-74
  
• Andrea Boni, Fabio Bardi:
  Intelligent hardware for identification and control of non-linear systems with SVM. 75-80
  

Novel neural transfer functions

• Wlodzislaw Duch, Norbert Jankowski:
  Transfer functions: hidden possibilities for better neural networks. 81-94
  
• Pawel Strumillo, Wladyslaw Kaminski:
  Neural networks with orthogonalised transfer functions. 95-100
  
• Norbert Jankowski, Wlodzislaw Duch:
  Optimal transfer function neural networks. 101-106
  
• Wlodzislaw Duch, Rafal Adamczak, Geerd H. F. Diercksen:
  Constructive density estimation network based on several different separable transfer functions. 107-112
  

ANN models and learning I

• Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
  Coding the outputs of multilayer feedforward. 113-118
  
• Mercedes Fernández-Redondo, Carlos Hernández-Espinosa:
  Weight initialization methods for multilayer feedforward. 119-124
  
• Michal Steuer, Praminda Caleb-Solly, Jim E. Smith:
  An alternative approach for the evaluation of the neocognitron. 125-130
  
• Martin Bogdan, Wolfgang Rosenstiel:
  Detection of cluster in Self-Organizing Maps for controlling a prostheses using nerve signals. 131-136
  

Neural networks and evolutionary/genetic algorithms - hybrid approaches

• Thomas Villmann:
  Evolutionary algorithms and neural networks in hybrid systems. 137-152
  
• Paulo Cortez, Miguel Rocha, José Neves:
  Lamarckian training of feedforward neural networks. 153-158
  
• Udo Seiffert:
  Multiple Layer Perceptron training using genetic algorithms. 159-164
  
• Karl-Theodor Kalveram, Ulrich Nakte:
  Motor control and movement optimization learned by combining auto-imitative and genetic algorithms. 165-170
  
• Fernando Fernández, Pedro Isasi:
  Designing nearest neighbour classifiers by the evolution of a population of prototypes. 171-178
  
• Jutta Huhse, Andreas Zell:
  Investigating the influence of the neighborhood attraction factor to evolution strategies with neighborhood attraction. 179-184
  
• I. Chalkiadakis, George A. Rovithakis, Michael E. Zervakis:
  A structural genetic algorithm to optimize High Order Neural Network architecture. 185-192
  
• Domingo Ortiz-Boyer, César Hervás-Martínez, José Muñoz-Pérez:
  Genetic algorithms with crossover based on confidence interval as an alternative to traditional nonlinear regression methods. 193-198
  
• Ignacio Rojas Ruiz, José Luis Bernier, Eduardo Ros Vidal, Fernando J. Rojas, Carlos García Puntonet:
  The synergy between multideme genetic algorithms and fuzzy systems. 199-204
  

ANN models and learning II

• Rudolph van der Merwe, Eric A. Wan:
  Efficient derivative-free Kalman filters for online learning. 205-210
  
• Adam I. Wilmer, Tania Stathaki, Steve R. Gunn, Robert I. Damper:
  Texture analysis with the Volterra model using conjugate gradient optimisation. 211-216
  
• Francesco Diotalevi, Maurizio Valle:
  Weight perturbation learning algorithm with local learning rate adaptation for the classification of remote-sensing images. 217-222
  

Neural networks in finance

• Eric de Bodt, Joseph Rynkiewicz, Marie Cottrell:
  Some known facts about financial data. 223-236
  
• Amaury Lendasse, John Aldo Lee, Eric de Bodt, Vincent Wertz, Michel Verleysen:
  Input data reduction for the prediction of financial time series. 237-244
  
• Vassilis S. Kodogiannis, A. Lolis:
  Prediction of foreign exchange rates by neural network and fuzzy system based techniques. 245-250
  
• Alex Aussem, C. Boutevin:
  Segmentation of switching dynamics with a Hidden Markov Model of neural prediction experts. 251-256
  

Data processing

• Michelangelo Diligenti, Marco Gori, Marco Maggini, Franco Scarselli:
  Searching the Web: learning based techniques. 257-264
  
• Victoria J. Hodge, Jim Austin:
  An integrated neural IR system. 265-270
  
• Thorsten Bojer, Barbara Hammer, Daniel Schunk, Katharina Tluk von Toschanowitz:
  Relevance determination in Learning Vector Quantization. 271-276
  
• Esa Alhoniemi, Olli Simula:
  Interpretation and comparison of multivariate data partitions. 277-282
  
• Barbara Hammer, Thomas Villmann:
  Input pruning for neural gas architectures. 283-288
  

Dynamical systems and chaos

• Brijnesh J. Jain, Fritz Wysotzki:
  On the short-term-memory of WTA nets. 289-294
  
• Nigel Crook, Tjeerd Olde Scheper:
  A novel chaotic neural network architecture. 295-300
  

Artificial neural networks and early vision processing

• Darryl Charles, Colin Fyfe:
  Unsupervised models for processing visual data. 301-308
  
• Magnus Borga, Hans Knutsson:
  Canonical correlation analysis in early vision processing. 309-314
  
• Tino Lourens, Kazuhiro Nakadai, Hiroshi G. Okuno, Hiroaki Kitano:
  A computational model of monkey grating cells for oriented repetitive alternating patterns. 315-322
  
• Stefan D. Wilke, Andreas Thiel, Christian W. Eurich, Martin Greschner, Markus Bongard, Josef Ammermüller, Helmut Schwegler:
  Extracting motion information using a biologically realistic model retina. 323-328
  
• Tino Lourens, Kazuhiro Nakadai, Hiroshi G. Okuno, Hiroaki Kitano:
  Graph extraction from color images. 329-334
  
• L. Tan, Colin Fyfe:
  Sparse Kernel Canonical Correlation Analysis. 335-340
  

ANN models and learning III

• Xavier Parra, Andreu Català:
  Learning fault-tolerance in Radial Basis Function Networks. 341-346
  
• César Hervás-Martínez, José Antonio Martinez Heras, Sebastián Ventura, Manuel Silva:
  A two steps method: non linear regression and pruning neural network for analyzing multicomponent mixtures. 347-352
  
• Tarek El. Tobely, Yuichiro Yoshiki, Ryuichi Tsuda, Naoyuki Tsuruta, Makoto Amamiya:
  SOM competition for complex image scene with variant object positions. 353-358
  
• Miguel A. Atencia Ruiz, Gonzalo Joya Caparrós, Francisco Sandoval Hernández:
  Numerical implementation of continuous Hopfield networks for optimization. 359-364
  
• Roelof K. Brouwer, Witold Pedrycz:
  One-to-many mappings represented on feed-forward networks. 365-370
  
• Gerald H. L. Cheang, Andrew R. Barron:
  Penalized least squares, model selection, convex hull classes and neural nets. 371-376
  
• Yoshifusa Ito, Cidambi Srinivasan:
  Bayesian decision theory on three layered neural networks. 377-382
  
• Joseph Rynkiewicz:
  Estimation of Hybrid HMM/MLP models. 383-390
  
• Patrice Wira, Jean-Philippe Urban, Julien Gresser:
  A divide-and-conquer learning architecture for predicting unknown motion. 391-396
  
• Emilio Corchado, Darryl Charles, Colin Fyfe:
  Rectified Gaussian distributions and the formation of local filters from video data. 397-402
  
• Elena Bellei, Diego Guidotti, Ruggero Petacchi, Leonardo Maria Reyneri, Italo Rizzi:
  Applications of neuro-fuzzy classification, evaluation and forecasting techniques in agriculture. 403-408
  

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