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ARTMED
2002
121views more  ARTMED 2002»
13 years 8 months ago
An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Hussein A. Abbass
ANNS
2010
13 years 4 months ago
Search Space Restriction of Neuro-evolution through Constrained Modularization of Neural Networks
Evolving recurrent neural networks for behavior control of robots equipped with larger sets of sensors and actuators is difficult due to the large search spaces that come with the ...
Christian W. Rempis, Frank Pasemann
ICANN
2010
Springer
13 years 10 months ago
Cell Microscopic Segmentation with Spiking Neuron Networks
Abstract. Spiking Neuron Networks (SNNs) overcome the computational power of neural networks made of thresholds or sigmoidal units. Indeed, SNNs add a new dimension, the temporal a...
Boudjelal Meftah, Olivier Lezoray, Michel Lecluse,...
CDC
2008
IEEE
152views Control Systems» more  CDC 2008»
14 years 3 months ago
Discrete-time sliding mode neural observer for continuous time mechanical systems
— This paper proposes a novel discrete­time veloc­ ity observer which uses neural network and sliding mode for unknown continuous time mechanical systems. The neural observer i...
Juan Resendiz, Wen Yu, Leonid M. Fridman
TNN
2008
177views more  TNN 2008»
13 years 8 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal