title: Neuromorphic function learning with carbon nanotube based synapses.
abstract: The principle of using nanoscale memory devices as artificial synapses in neuromorphic circuits is recognized as a promising way to build ground-breaking circuit architectures tolerant to defects and variability. Yet, actual experimental demonstrations of the neural network type of circuits based on non-conventional/non-CMOS memory devices and displaying function learning capabilities remain very scarce. We show here that carbon-nanotube-based memory elements can be used as artificial synapses, combined with conventional neurons and trained to perform functions through the application of a supervised learning algorithm. The same ensemble of eight devices can notably be trained multiple times to code successively any three-input linearly separable Boolean logic function despite device-to-device variability. This work thus represents one of the very few demonstrations of actual function learning with synapses based on nanoscale building blocks. The potential of such an approach for the parallel learning of multiple and more complex functions is also evaluated.
authors.affiliation: CEA, IRAMIS, Service de Physique de L’Etat Condensé (CNRS URA 2464), Laboratoire d’Electronique Moléculaire, Gif-sur-Yvette, France.
authors.forename: Karim
authors.initials: K
authors.lastname: Gacem
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Retrouvey
authors.forename: Djaafar
authors.initials: D
authors.lastname: Chabi
authors.forename: Arianna
authors.initials: A
authors.lastname: Filoramo
authors.forename: Weisheng
authors.initials: W
authors.lastname: Zhao
authors.forename: Jacques-Olivier
authors.initials: JO
authors.lastname: Klein
authors.forename: Vincent
authors.initials: V
authors.lastname: Derycke
mesh_terms: D004581:Electronics; D008959:Models, Neurological; D036103:Nanotechnology / Q000295:instrumentation*; D037742:Nanotubes, Carbon; D016571:Neural Networks, Computer; D013569:Synapses
chemical_list: D037742:Nanotubes, Carbon