Abstract. Complex networks like the scale-free model proposed by BarabasiAlbert are observed in many biological systems and the application of this topology to artificial neural ne...
Mauro Annunziato, Ilaria Bertini, Matteo De Felice...
Artificial Neural Networks are universal and highly flexible function approximators first used in the fields of cognitive science and engineering. In recent years, Neural Networks...
An efficient algorithm to train general differential recurrent neural networks is proposed. The trained network can be directly used as the internal model of a predictive controll...
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
We present a biologically inspired neural network model of visual orienting (using saccadic eye movements) in which targets are preferentially selected according to their reward va...