Evolution of plastic learning in spiking networks via memristive connections
(2012)
Journal Article
This paper presents a spiking neuroevolutionary system which implements memristors as plastic connections, i.e., whose weights can vary during a trial. The evolutionary design process exploits parameter self-adaptation and variable topologies, allowi... Read More about Evolution of plastic learning in spiking networks via memristive connections.