Abstract— Hardware implementations of Spiking Neural Networks are numerous because they are well suited for implementation in digital and analog hardware, and outperform classic ...
Benjamin Schrauwen, Michiel D'Haene, David Verstra...
Abstract— Supervised learning rules for spiking neural networks are currently only able to use time-to-first-spike coding and are plagued by very irregular learning curves due t...
Abstract. We describe a set of preliminary experiments to evolve spiking neural controllers for a vision-based mobile robot. All the evolutionary experiments are carried out on phy...
— The detection of transient responses, i.e. non– stationarities, that arise in a varying and small fraction of the total number of neural spike trains recorded from chronicall...
This paper investigates the evolution of autonomous agents that solve a memorydependent counting task. Two types of neurocontrollers are evolved: networks of McCulloch-Pitts neuro...