Title :
Memcapacitive neural networks
Author :
Pershin, Yuriy V. ; Di Ventra, Massimiliano
Author_Institution :
Dept. of Phys. & Astron., Univ. of South Carolina, Columbia, SC, USA
Abstract :
It is shown that memcapacitive (memory capacitive) systems can be used as synapses in artificial neural networks. As an example of the proposed approach, the architecture of an integrate-and-fire neural network based on memcapacitive synapses is discussed. Moreover, it has been demonstrated that the spike-timing-dependent plasticity can be simply realised with some of these devices. Memcapacitive synapses are a low-energy alternative to memristive synapses for neuromorphic computation.
Keywords :
micromechanical devices; neural nets; artificial neural networks; integrate-and-fire neural network; memcapacitive synapses; memory capacitive systems; neuromorphic computation; spike-timing-dependent plasticity;
Journal_Title :
Electronics Letters
DOI :
10.1049/el.2013.2463