Organic memristive device is an element specially constructed for mimicking synapse properties. Its working principle is based on the significant difference of conducting polymers properties (polyaniline, in particular) when they are in the reduced and oxidized states. Initially, it will be described the architecture and properties of organic memristor. Then, the logic elements with memory will be introduced. The analogy with synapses will be demonstrated showing the artificially realized circuit, mimicking a part of the nervous system of the pond snail, responsible for the learning of this animal during feeding. Organic memristive devices are in places of synapses of the snail model and the circuit was able to make the association of the neutral stimulus (touching of lips) with the presence of food. Finally, it will be described a stochastic network, composed from block-copolymers, polyaniline and gold nanoparticles. Several similarities of the network properties and nervous systems have been observed. In particular, applying different training algorithms, the system revealed features, similar to 'adult' and 'baby' (imprinting) learning. © 2013 IEEE.
Organic memristive devices: Architecture, properties and applications in neuromorphic networks
Erokhin;Victor
2013
Abstract
Organic memristive device is an element specially constructed for mimicking synapse properties. Its working principle is based on the significant difference of conducting polymers properties (polyaniline, in particular) when they are in the reduced and oxidized states. Initially, it will be described the architecture and properties of organic memristor. Then, the logic elements with memory will be introduced. The analogy with synapses will be demonstrated showing the artificially realized circuit, mimicking a part of the nervous system of the pond snail, responsible for the learning of this animal during feeding. Organic memristive devices are in places of synapses of the snail model and the circuit was able to make the association of the neutral stimulus (touching of lips) with the presence of food. Finally, it will be described a stochastic network, composed from block-copolymers, polyaniline and gold nanoparticles. Several similarities of the network properties and nervous systems have been observed. In particular, applying different training algorithms, the system revealed features, similar to 'adult' and 'baby' (imprinting) learning. © 2013 IEEE.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


