We provide characterizations of the relations that can be computed with arbitrary knowledge on networks where all processors use the same algorithm and start from the same state (...
Radial basis function networks (RBF) are efficient general function approximators. They show good generalization performance and they are easy to train. Due to theoretical consider...
Since the classical work of D. O. Hebb [1] it has been assumed that synaptic plasticity solely depends on the activity of the pre- and the postsynaptic cell. Synapses influence th...
Abstract— In this paper, we present an effective computational approach for learning patterns of brain activity from the fMRI data. The procedure involved correcting motion artif...
Yizhao Ni, Carlton Chu, Craig J. Saunders, John As...
— Exploratory activities seem to be crucial for our cognitive development. According to psychologists, exploration is an intrinsically rewarding behaviour. The developmental robo...