A method to extract a fuzzy rule based system from a trained artificial neural network for classification is presented. The fuzzy system obtained is equivalent to the correspondin...
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...
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 ...
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,...
— 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...