Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses.
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ABSTRACT:
SUBMITTER: Serb A
PROVIDER: S-EPMC5056401 | biostudies-literature | 2016 Sep
REPOSITORIES: biostudies-literature
Publications
Unsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses.
Serb Alexander A Bill Johannes J Khiat Ali A Berdan Radu R Legenstein Robert R Prodromakis Themis T
Nature communications 20160929
In an increasingly data-rich world the need for developing computing systems that cannot only process, but ideally also interpret big data is becoming continuously more pressing. Brain-inspired concepts have shown great promise towards addressing this need. Here we demonstrate unsupervised learning in a probabilistic neural network that utilizes metal-oxide memristive devices as multi-state synapses. Our approach can be exploited for processing unlabelled data and can adapt to time-varying clust ...[more]
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