Information in the nervous system has often been considered as being represented by simultaneous discharge of a large set of neurons. We propose a learning mechanism for neural inf...
Abstract. This article underlines the learning and discrimination capabilities of a model of associative memory based on artificial networks of spiking neurons. Inspired from neuro...
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
A major issue in evaluating speech enhancement and hearing compensation algorithms is to come up with a suitable metric that predicts intelligibility as judged by a human listener...
Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Ha...
We designed subthreshold analog MOS circuits implementing an inhibitory network model that performs noise-shaping pulse-density modulation with noisy neural elements. Our aim is t...