  We show that memcapacitive (memory capacitive) systems can be used as
synapses in artificial neural networks. As an example of our approach, we
discuss the architecture of an integrate-and-fire neural network based on
memcapacitive synapses. Moreover, we demonstrate that the
spike-timing-dependent plasticity can be simply realized with some of these
devices. Memcapacitive synapses are a low-energy alternative to memristive
synapses for neuromorphic computation.
