default search action
ESANN 1994: Brussels, Belgium
- 2nd European Symposium on Artificial Neural Networks, ESANN 1994, Brussels, Belgium, April 20-22, 1994, Proceedings. 1994
Neural networks and chaos
- Thorsten Kolb, Karsten Berns:
Concerning the formation of chaotic behaviour in recurrent neural networks. - William G. Gibson, John Robinson, Christopher M. Thomas:
Stability and bifurcation in an autoassociative memory model.
Theoretical aspects I
- Joan Codina, Juan Carlos Aguado, Josep M. Fuertes:
Capabilities of a structured neural network. Learning and comparison with classical techniques. - Konrad Weigl, Marc Berthod:
Projection learning: alternative approaches to the computation of the projection. - Ziqiang Mao, Tien C. Hsia:
Stability bounds of momentum coefficient and learning rate in backpropagation algorithm.
Links between neural networks and statistics
- Guido M. te Brake, Joost N. Kok, Paul M. B. Vitányi:
Model selection for neural networks: comparing MDL and NIC. - Pierre Comon, Jean-Luc Voz, Michel Verleysen:
Estimation of performance bounds in supervised classification. - Igor V. Tetko, Alexander I. Luik:
Input Parameters' estimation via neural networks. - Enrica Filippi, Mario Costa, Eros Pasero:
Combining multi-layer perceptrons in classification problems.
Algorithms I
- J. Iwanski, J. Schietse:
Diluted neural networks with binary couplings: a replica symmetry breaking calculation of the storage capacity. - Geert Jan Bex, Roger Serneels:
Storage capacity of the reversed wedge perceptron with binary connections. - Francisco Javier López Aligué, Miguel A. Jaramillo Morán, M. Isabel Acevedo Sotoca, Montserrat García del Valle:
A general model for higher order neurons. - Bojan Petek:
A discriminative HCNN modeling.
Biological models
- Gregory R. Mulhauser:
Biologically plausible hybrid network design and motor control. - W. Mommaerts, Edward C. van der Meulen, Tatyana S. Turova:
Analysis of critical effects in a stochastic neural model. - Jean-Pierre Rospars, Petr Lánský:
Stochastic model of odor intensity coding in first-order olfactory neurons. - Alexander S. Mikhailov:
Memory, learning and neuromediators. - François Chapeau-Blondeau, Nicolas Chambet:
An explicit comparison of spike dynamics and firing rate dynamics in neural network modeling.
Algorithms II
- Berthold Ruf:
A stop criterion for the Boltzmann machine learning algorithm. - Manuel Graña, Víctor Lavín Puente, Alicia D'Anjou, Francisco X. Albizuri, José Antonio Lozano:
High-order Boltzmann machines applied to the Monk's problems. - Frédéric Aviolat, Eddy Mayoraz:
A constructive training algorithm for feedforward neural networks with ternary weights. - Tatyana Luzyanina:
Synchronization in a neural network of phase oscillators with time delayed coupling.
Evolutive and incremental learning
- Samira Sehad, Claude F. Touzet:
Reinforcement learning and neural reinforcement learning. - Juan Manuel Moreno, Francisco Castillo, Joan Cabestany:
Improving piecewise linear separation incremental algorithms using complexity reduction methods. - Olivier Fambon, Christian Jutten:
A comparison of two weight pruning methods. - Claude F. Touzet:
Extending immediate reinforcement learning on neural networks to multiple actions. - Jacques Ludik, Ian Cloete:
Incremental increased complexity training.
Function approximation
- Vera Kurková, Katerina Hlavácková:
Approximation of continuous functions by RBF and KBF networks. - Michel Verleysen, Katerina Hlavácková:
An optimized RBF network for approximation of functions. - Valeriu Beiu, J. A. Peperstraete, Joos Vandewalle, Rudy Lauwereins:
VLSI complexity reduction by piece-wise approximation of the sigmoid function.
Algorithms III
- Axel Röbel:
Dynamic pattern selection for faster learning and controlled generalization of neural networks. - John A. Bullinaria:
Noise reduction by multi-target learning. - Antony Browne, John R. Pilkington:
Variable binding in a neural network using a distributed representation. - Marcello Chiaberge, Juan Julián Merelo Guervós
, Leonardo Maria Reyneri, Alberto Prieto, L. Zocca:
A comparison of neural networks, linear controllers, genetic algorithms and simulated annealing for real time control. - Raúl Rojas:
Visualizing the learning process for neural networks.
Theoretical aspects II
- Yonghong Tan, Mia Loccufier, Robin De Keyser, Erik Noldus:
Stability analysis of diagonal recurrent neural networks. - Tom Heskes:
Stochastics of on-line back-propagation. - Nicolas Pican, Jean-Claude Fort, Frédéric Alexandre:
A lateral contribution learning algorithm for multi MLP architecture.
Self-organization
- Marie Cottrell, Jean-Claude Fort, Gilles Pagès:
Two or three things that we know about the Kohonen algorithm. - Marlene Alvarez, A. Varfis:
Decoding functions for Kohonen maps. - Heike Speckmann, Günter Raddatz, Wolfgang Rosenstiel:
Improvement of learning results of the selforganizing map by calculating fractal dimensions. - Jean-Claude Fort, Gilles Pagès:
A non linear Kohonen algorithm. - Andreas Kanstein, Karl Goser:
Self-organizing maps based on differential equations. - Ralf Der, J. Michael Herrmann:
Instabilities in self-organized feature maps with short neighbourhood range.
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
last updated on 2024-12-08 01:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: